Tableau Full Course 2026 [FREE] | Tableau Data Visualization Course | Tableau Tutorial | Simplilearn

Key Takeaways

Did you know that over 30 million people worldwide are using Tableau to turn complex data into actionable insights? From small startups to Fortune 500 companies, Tableau is helping businesses make datadriven decisions that drive growth, innovation, and efficiency. So, welcome to the Tableau Desktop Specialist Certification Training. I'm excited to guide you through this hands-on course where you will learn how to harness the power of data visualization and become proficient in using Tableau to solve real business challenges. Whether you're just starting out or looking to level up your skills, this course will give you the tools and the techniques that you need to stand out in the world of data analytics. So, first we'll start with an introduction to Tableau and explore how it's transforming industries by turning raw data into insightful visuals. Then we will dive into setting up your first Tableau project and teach the essentials while navigating the Tableau interface. Next, we will learn how to create impactful visualizations that help you tell a story with your data. Then we will cover how to connect Tableau to different data sources for preparing your data for analysis. Then you will get hands-on with advanced techniques like calculated fields, filters, and building interactive dashboards. We will then explore how to share your work with others by publishing and presenting your Tableau dashboards. Finally, we'll wrap up with the industry case studies demonstrating how companies are leveraging Tableau to achieve their business goals. So, if you're interested in building a strong career in data analytics, I highly recommend that you check out their data analyst certification course by simply learn. This course gives you an industry recognized master certificate from SimplyLearn along with individual certificates from Microsoft that you can showcase to potential employers. A real boost for your resume. You will master key tools like Excel, SQL, Python, Tableau, and PowerBI. Work on real projects to build practical skills and learn how to turn raw data into insights that drive better business decisions. Plus, Job Assist support will help you prepare for interviews and get noticed by top hiring companies. This course is designed to help you gain the skills and confidence needed to step into the high demand data roles. So, if you're serious about a data career, this program is definitely worth exploring. >> Here in Google, if you type Tableau Desktop download, okay, just type desktop download. Yeah, Tableau Desktop download. You type over here in Google and then you can go to uh this area this link that is download Tableau desktop. Okay, you can click the link here. After typing Tableau desktop download. So just like PowerBI you are also having here uh Tableau Desktop. Okay, we there we had Power PowerBI desktop here we are having uh Tableau desktop. So if you click this link here after typing Tableau desktop download Tableau Desktop then here you'll come to this area. It says here Tableau Desktop start your free 14-day trial. Now see here I'll be telling you the difference. Okay, the first difference is coming over here between the PowerBI desktop and Tableau Desktop. See PowerBI desktop as you know that it's a free tool. So it's a uh free for the lifetime. Okay. So that's the best part of PowerBI. But Tableau Desktop is having a 14-day trial period. So after 14 days you have to pay money. So here uh it says download free trial. Okay, definitely we have to go for this one. Download free trial and then when you click on that download free trial and then the free trial should get downloaded. Okay. Okay. It should get downloaded over here. Yeah. So it will take some time here and once it get downloaded in your system then please double click that exe file and then you install. Okay. you agree to the terms and conditions and then uh you click on install and then it will get installed. Okay. So installation also will take some time. I would like to tell you one important thing here that Tableau desktop as we know that Tableau desktop is having a uh 14-day trial period. Okay. Now the question will come that okay what should I do after 14 days? So if you are a student, okay, now listen to this thing very clearly. If you are a student in a university then you can get a free license for this Tableau desktop for one year. Okay, you'll be getting a one-ear free license if you are a student or if you are a university professor. Okay. So only for these two categories there's a free license either for the university professor or for the student. So if you are a student then what you can do that simultaneously I'm not saying that you wait for 14 days and then you apply for the student license. What you can do here in Google if I let me make it bigger for you. So here you write down Tableau desktop. Yeah, you see here in my case it is showing me here Tableau desktop download student. Okay, so Tableau desktop download student. If I click it then here it will take me to you I have to go to this area Tableau for student. If I click it Tableau for student. So see this is the page. If you want I can also put it in the chat window here. Yeah. So I put up the link in the chat window. You can also use this link if you are a student. And then here it says download Tableau Desktop and Tableau prep builder. Okay. Now what is this Tableau Tableau prep builder that I'll be talking in the presentation here. So here it says get Tableau for free. Okay. So suppose if I click this link here then what it will ask you here it says uh full-time students at accredited credit bearing academic institutions worldwide are eligible for a free one-year license to activate Tableau Desktop and Tableau Prep. Okay. So you'll be getting the license for two products of Tableau. One is Tableau Desktop and Tableau Prep. In this training program we'll be focusing only on Tableau Desktop. We will not be using Tableau Prep but it is good that you are having also Tableau Prep. Yeah. Complete the form below to confirm your eligibility and unlock your free license. You must be 16 years of age or older to request a license. So here in this form you have to give all the details. Okay. Also here it requires your school issued email. So here if you type your email id let's say if I type my email I id summi roadia@gmail.com it will not accept. Yeah, because it has to be Sami Roia something university uh edu or something like that. So I have to give my university email id not the common email id. Yeah, general email id yahoo mail or Gmail. So I have to give this my uh university mail ID. Yeah, date of birth blah blah blah school and everything. And then you it will you click this button verify student status and then the details will go to the tableau. If required your Tableau will also ask you to uh send the uh this uh your u university ID okay your identity card. It will also tell you to scan that university identity card and send it to them. or sometime they may say okay but I would say that today only you apply for this license okay and then you can uh uh wait for it and maybe once the new year is there then you'll be getting the license okay these are the important things okay the Tableau desktop is uh in general it is having 14 days trial period now say suppose if you are if you want to pay for this Tableau license definitely I'll not tell you to pay for that amount uh say pay for this Tableau desktop but uh the normal costing of Tableau desktop is around $70 or $70 per month per user basis yeah so every month you have to pay $70 or €70 that's the price okay so here I would say that Tableau is having some issue when I compare with PowerBI because PowerBI desktop free tool you get every month new new versions and uh you are not paying anything for that but uh Tableau Desktop you have to pay money okay but now I'll show you also show you those who are not university professors or those who are not university students what you can do that see currently if you have downloaded the latest version So currently the version which is there for the Tableau desktop it is uh 2024. Let me show you that part. Yeah. So this is the Tableau desktop which I have already opened. Yeah. So here if I go to help and then about Tableau. So currently I'm having this today only I downloaded this latest version. it is 2024 3.1 okay so uh now see what happens that suppose after 14 days if you are this Tableau desktop trial will get over so what I'll suggest you that those who are not university professors or those who are not students you can first of all remove the current Tableau desktop from your system okay whatever you have installed you remove that portion Yeah. Uh and then again what you do you go to Google and in Google you type here Tableau desktop Tableau desktop older versions. Tableau desktop older versions. So if you type over here Tableau desktop older versions then here you can go to this area here. Yeah. See Tableau is a now a uh uh say part of Salesforce company. Okay, we'll talk about that part in the theory. But uh here it is showing you Salesforce. So here it says downloading previous versions of Tableau desktop. So suppose if I click this thing. So here it comes to downloading previous versions of Tableau desktop or server. I'll go to this area. Go to downloads and release note. I click on this portion downloads. Now see here these are all the see the current version is 2024.3.1. Okay. If you want I can also share this link in the chat window. Yeah. If you want to come over here you can you can click the link in the chat window. So the current version is 2024.3.1. Now suppose if this version you have already installed and now it is over the trial period is over then you remove this version from your system from from your laptop and then you come over here to this page you can save this page for a reference purpose and now see it is 2024.3 if I click this one so see in 2024.3 there are again two versions okay this is the latest version 3.1 1 and uh that was released in November 21 and before that this new version was also there another version was also there that is 2024.3 so what you can do you can now come to this area in on this page and you can click this this version here 2024.3 and then you install this version the older version the next the uh next older version you install it and then again use it for 14 is okay I know that this is a tedious process but this is how you can save your money okay so otherwise if you are ready to pay $70 or $70 I don't mind but this is what I I I normally recommend uh to the participant that you can go to the next older version so now if you download this uh version and if you use it for 14 days again you remove that version again you come to this area now you can go to 2024.2 or two. Now see up till if you are going till uh let's say 2023 also this particular this version then you don't have any problem okay because normally we think that oh I if I'm going to the older version then definitely I'll be not having all the latest features but as such in Tableau this is my personal feeling that in Tableau they are not changing so much things in Tableau okay in PowerBI what happened that every version is having something new but in Tableau So the changes are not that much drastic. So even if you one by one if you go see for 2024.2 also if you click it there are so many versions. You can use this version for every version you can use it for 14 days. Okay. Likewise 2024.1 and so on. Okay. So this is how you can save your money and at least I would say that see just now you have to focus on this course. Okay. you try to have this Tableau desktop for this course. Okay. And then after the course is over, if you are in the organization and if you want to uh do something more with the Tableau, then definitely you can ask your organization and they will pay the money for you. Okay. But at least just now for this course you have to go like this. Okay. Those who are not having this now this is Tableau desktop. Okay. So in case of Tableau they also have one more version uh another tool which is known as Tableau public. So suppose if I write down here Tableau public download. Okay Tableau public download. Now what is this Tableau public here? Tableau public remember that it's a free version. Okay. And it is free for the lifetime. Just like Tableau uh just like PowerBI desktop here they are having Tableau public. So here you don't pay anything and here you don't have any problem of trial period. Okay. So this is also another tool especially for this training I would say for especially for this training you can go for Tableau public also. Okay. So I I'll tell you what is the limitation over here definitely because whatever is free it is yeah there is no free lunch in this world as we know. So whatever is free it will not have all the features but I'll tell you yeah the exact difference over here but Tableau public also uh what I I would suggest you that just now you go for Tableau Desktop you use it for 14 days after 14 days if you want to still use Tableau Desktop I already shown you the method of going to the older versions if not then you can come to this Tableau public and here we are having this link Tableau test uh download Tableau public if I click it okay so normally here I I I think so I I'll show you exact link because somewhere you'll be finding the link here the Tableau public uh Tableau public here let me see yes this is the Tableau public Tableau public is a free platform to explore create and publicly share data visualiz izations online with the largest repository of blah blah blah. Uh yeah, Tableau public makes data skills this thing. Okay. So this is the button tableau public may maybe you can also download this parallelly along with your Tableau desktop also because see sometimes if your Tableau desk if your Tableau desktop is over at least you are having the backup of Tableau public I would say. Yeah. So this also you download immediately. Yeah. Click on this link. Go to Tableau Public and then definitely here also it will ask you to sign in. Yeah, here it says sign up for Tableau Public. If I click it, then here I have to just I have to give here my first name, last name, email. Now see here email you can give uh your Gmail or Yahoo mail also. Okay, here they don't require a professional mail ID. So in the Tableau public you can if you want to create your account you can create your account with your Gmail ID or Yahoo mail ID or any or other general mail. Okay. So give your last name, first name, email, password, concern password and it will create a account and then from there it will start downloading. Okay, maybe after you put all these details then it will show you download Tableau test download Tableau public. You click on that button and then it will download that Tableau public and then you install it. Okay. So two tools you have to install one by one today. Tableau desktop and Tableau public. Benefits of data visualization. Let us quickly see. So quick and clear understanding of the information. As I said as as I mentioned earlier that whenever you see a visualization you are able to get the information very quickly and you are also able to remember that visualization. So quick and clear understanding of the information. Second benefit of data visualization is identify emerging trends and act quickly based on what we see. Yeah. So this is a great benefit of data visualization identifying emerging trends. Now see whenever I'm conducting the sessions uh let's say powerba sessions or tableau sessions for the mostly for the US and Canadian participants yeah on another platform. So there I always give the example uh in this second point I give the example of uh India. Okay that we were I think so this also we discussed maybe in the business analytics portion also uh business analytics with Excel that after the covid two major things happened in India. First one was the digital payment. Yeah, everywhere people were just scanning the QR code or barcode and they were paying the money. Yeah, it was which was great and up till now also the things are going on very well. And the second thing was this online sessions. Yeah, especially for the universities because I was associated with many universities but I was not able to conduct the online sessions before the covid. Yeah, because there was no trend. I was I I'm not saying that there was no technology there was no trend of conducting the online sessions in the university especially yeah for this kind of simply learn courses and this this we were having the things but for university there were no online courses uh online sessions so that also happened yeah thanks goes to covid and uh since 20 uh 20 yeah after this covid uh I'm regularly conducting the online sessions for the students students also for the university students okay up till now. So that is the major thing which has happened and for the digital payment. Okay, I always give this digital payment example even to my German colleagues also that here in Germany also still people are believing in the hard cash. Many people though definitely many or many of the shops they are they are taking the uh credit cards and debit cards but uh still many people they are having the uh cash. Okay, they believe in cash. Even just now we are having the Christmas uh uh market and all those things. In Christmas market I don't know hardly I have seen one or two stores uh one or two yeah shops over here in the Christmas market with their uh okay where they are accepting the uh credit cards or debit cards otherwise it's fully on the cash. I don't know about other countries yeah whether the same thing is there but here mostly people are going for the cash. So what happened that when that covid came so it it brought many challenges. Yeah. And those who accepted those challenges and they came out with some solution they are still there in the market. Yeah. I I remember that I'm coming from uh city known as Vodra in Gujarat and uh uh earlier when I used to visit my city my state uh I used to go to some specific restaurants okay uh so uh yeah because they were famous for good food but when I went after covid many of those my good restaurants they were closed down they were completely shut down okay I don't know what was the reason but one of the reason was that what I came to know was that they did not accept it the new change. Yeah. Initially people they were not going to the restaurants they were having everything online. Yeah. Everything was delivered. Uh but these restaurants they some of somehow they insisted that no no we should we have to uh bring here the people rather than the delivery. So those who did not accepted the change they were out of the market. And also it happened in my city that many of the new restaurants also got opened during the covid time and they are still there. Yeah. Because they accepted this new trend. Okay. So whatever this example which I'm giving here, this example also applies to us. Yeah. to our our own life that if whatever the new things which are coming in the data analytics or business analytics if we are not accepting those changes we'll be also out of the market yeah just like those restaurants so today we are talking about generative tomorrow we'll be talking about something else we have to continuously learn these new tools that is what is my thing okay and I and I'm also doing the same thing yeah so emerging trends we can quickly identify with the help of data visualization and we can implement it. Then the number three is identify the relationships and patterns. So we can see that okay if our sales have gone down then why the sales have gone down what are the reasons for that lower sales so that we can easily identify with the visualization. The fourth benefit over here is share our story with others. So share our story with others. Now what is this story here? Story means we are talking about the report or the dashboard. Yeah. Now you know that in every organization everybody will not be creating the dashboard. Everybody will not be creating the PowerBI report. Few people will be creating the report and the other people will be utilizing that report. Yeah. So here sharing our story means if I create my uh report then definitely I have to share with my colleagues. So I have to share my story with other people. So in case of Tableau also I'll be showing and in Tableau uh it is little bit different compared to PowerBI. Yeah. So that also we'll discuss that where this PowerBI and Tableau are different in terms of creating the report and creating the dashboard. Okay. So when that particular topic will come up I'll tell you these differences. Number fifth is analysis at various levels of details. analysis at various levels of details means suppose if I'm having if I'm working in a MNC company so definitely I'll be having the uh we were talking about this analysis at various levels of details so we start from US from US we go to the state from state we go to the city and and within the city also we are having the various areas so we are having the postal code or pin code so we go to that area level so this is what we mean by analysis at various levels of detail and in short it is known as hierarchy key. Okay. So that is that hierarchy topic and the last point over here the last benefit is improved customer experience and engagement. Now whatever we have uh seen up till now all the benefits why we are doing all those things why we are sharing our story why we are doing the analysis at various levels of detail because we want to give the best experience to our customer. We want to make them satisfy we want or or we want to make them happy. Yeah. Because if the customers are happy, if the customers are engaged with our company, overall we are also happy. It's a win-win situation. So in general, these are the benefits of data visualization. No. Now I'll not talk about PowerBI just skip this thing. But what I wanted to show you here that this is the uh magic quadrant. I don't know whether you saw it in your PowerBI course. This is the magic quadrant for analytics and business intelligence platform. Now who has created this magic quadrant? The magic quadrant has been created by this company known as Gartner. Okay. So Gartner I think so you must have heard this company name. If not then I would like to uh inform you that this Gartner is a very famous research company. They are conducting lot of research over here. So they are every year they are creating their own report and then there are companies who are buying those reports. Okay, these reports are not free of cost. You have to pay for it. So here I want to highlight that what is the scenario of those various data visualization products that we are having in the market. So this is the scenario which was there in 2022. Yeah. So we'll see the scenario of 2022, 2023 and the latest scenario in 2024. So in 2022 you can see that the in this magic quadrant we are having these four quadrants. So we are having the leader section, challenger section, niche players and the visionaries. If you focus on the leader section, the leaders in this data visualization area here it is written Microsoft and then it is written here Salesforce bracket Tableau and the third leader is click. I'm sure that you must have heard this click company. Click is a very famous data visualization company in US but uh they are their products are used worldwide. So click is having two products. Initially they were having click view. Click view and the latest product is the clicksense. Yeah. So I have also learned that tool clicksense and click view. Though not though I'm not using regularly here. Now here comes Microsoft. Now see I I initially told you that PowerBI is currently number one tool in the data visualization market. But now see here it is not written PowerBI. It is written here Microsoft. Why Microsoft? Why it is written Microsoft? Because definitely Microsoft is not having one tool that is PowerBI. But if I just talk about data visualization tool then the data visualization tool Microsoft is having two products. First one is Excel as we know very well and the second one is PowerBI. Okay. So Excel came almost like 30 years before or 30 35 years before. So and today also people are still using Excel for the data analysis for visualization purpose everything. So that's why here they have not specifically mentioned PowerBI but they have mentioned here Microsoft. Yeah. But overall I would say that I I'll repeat that sentence that PowerBI is currently number one tool in the data visualization market. Then comes Tableau and then comes click and then these are the other tools. You see that I was talking about this tool micro strategy in 2022. It was in the niche player segment. Yeah. Then Google was here challenger section. Google is having Google looker studio. Initially Google changed the name to Google data studio but then last year sorry this year only they changed it to Google looker studio. So I have also learned that tool. Yeah. So see that is the advantage that I that we also all all get there seeing that if you know one tool you can learn the other tools very easily. Yeah just remember that their look and feel effect is different and definitely some of the features which are available in PowerBI will not be available in Tableau or the features which are available in Tableau they will not be available in PowerBI. So you have to understand only those features which are not common. Now in 2023 what was the scenario? The scenario was same. Microsoft was number one. Salesforce tableau was number two and click was number three. Yeah. Here little bit you can see that this micro strategy which was in n player now it has shifted to challengers. It shifted to challengers here in 2023. Yeah. Maybe this Alibaba also Alibaba cloud it also came over here. So some changes occurred over here. Now let us focus on 2024 the current year. So in current year you see here the scenario leader section see so many leaders are now here Microsoft Tableau click is over here Google has come now here yeah now so now I know that some of the companies have shifted to Google local studio because it is also cheaper yeah the everything comes to the price initially then we are having here Oracle and thspot. Thot is also a great is a tool famous tool. So see now you can see that Tableau is facing lot of competition here. Definitely it is also uh this powerb also facing competition but here all these tools are nearby tableau. Yeah. So whenever a company wants to decide which is the best tool or which is the second best tool then now company has to think over these other tools also. So that's why when I saw this this figure for the first time I was really astonished because till 2023 and 2022 you see the 2022 2023 the scenario will almost same especially for the leader section but as soon as we went to 2024 the things change here and now I don't know what will happen in 2025 maybe some other one or two tools will come over here you never know so this is what I wanted to highlight here that is uh how this data visualization market is uh is moving. So now we'll be focusing really on the topic of Tableau. Okay. So Tableau data visualization tool. Okay. And it is very popular among the users. Now what it says here Tableau allow us to evaluate raw data in the form of graphs and report. Yeah. So initially we create some some graph or some charts and then what we do then we put all those graphs and charts into one particular page and that page is known as dashboard. Okay just I would like to ask you one question here that you have all used PowerBI desktop. Okay. So I would like to ask you one question that whatever the visualizations you are creating in PowerBI desktop that whole file okay that whatever that PowerBI file that you are creating PowerBI desktop file which you which you're creating yeah that is that is having an extension of PBXIX. So what is that PowerBI file known as? That's my question. Yeah that PowerBI file is having many pages. You must have created various pages. So what is the name given to that that whole concept of that file? Okay. What is that whole file known as? PowerBI. So it's known as report. Yeah. So that should be very clear. That whole PowerBI file which we create in the PowerBI desktop, it is known as PowerBI report. Why I'm stressing this point? Because many people they also mention it as a dashboard. that is not a dashboard. Okay. In PowerBI desktop you cannot create a dashboard and and normally the dashboard is of one page only. Dashboard will have only one page. While in the PowerBI file we are creating various pages. So that is known as a report. Okay. So you should be very clear over here. Yeah. Now I would like to ask you that where we can create dashboard in PowerBI. Suppose if I want to create a dashboard in PowerBI where should I create? Okay. So now the answer for this question is this that where I can create the PowerBI dashboard. PowerBI dashboard can be created only in PowerBI services. I repeat PowerBI dashboard can only be created in PowerBI services. It cannot be created in PowerBI desktop. In PowerBI desktop, we create only PowerBI report. Yeah, that's why I asked this question. I wanted to clear this confusion. Yeah, because many people they say oh see many people they feel that dashboard and report are same. No, in case of PowerBI it is totally different. Yeah. So you must have uh yeah in your uh online session you must have been shown that how we can create a dashboard in the PowerBI services. Yeah I hope that you must have been shown this thing. Yeah how to create the dashboard in PowerBI services if I'm not wrong. Yeah that you should know the concept. Okay. So uh dashboards are always created in PowerBI services that PowerBI services as you know that it's an online platform. Okay. Where suppose if I want to uh share my uh report with my colleague then I have to uh publish that PowerBI report into the PowerBI services and then from there powerbased services I can provide the access. I can say that okay I want to give access to let's say Dsha. Okay. So I'll write down the email id of Dsha or let's say Clifton or Henry or whoever. Yeah. And then uh you'll be able to see my uh report in the thing and uh dashboard also I can create in the PowerBI services and uh what I do that from the PowerBI report I can take some few visualizations from the report and I can put it into the dashboard. Okay. So this is what is PowerBI. Okay. Now in case of Tableau in Tableau we don't have the concept of Tableau report we have the concept of in Tableau we'll be now uh mostly tomorrow onwards we'll try to see that in Tableau what happened that on one page I can create one visualization I repeat on Tableau in Tableau desktop or in Tableau public whichever you tool you use on one sheet yeah I I can create only one visualization while in case of PowerBI in on one page you can create many visualizations. Yeah. So that is where the difference now is coming up here. Yeah. So in case of Tableau I create 10 sheets. 10 sheets means 10 visualizations let's say. And then in the T table Tableau desktop or Tableau public I'm having a separate section which is known as Tableau dashboard. So Tableau dashboard if I want to create I don't have to go to any other online platform. I can do it in the Tableau desktop or Tableau public. So in the Tableau dashboard I bring all the visualizations. Okay. And I I can put it into one place and that is what is meant by Tableau dashboard. Okay. So here this difference comes up between the between the PowerB and Tableau. Yeah. So that is what so here in case of Tableau also we'll be creating these kind of a yeah here they have used the word report but it's not actually the report it's a tableau dashboard where you can bring all the visualizations together data can be in the form of big data Hadoop SQL cloud based plat uh cloud data anything can be there okay and and all the data can be brought into Tableau that we'll see further in the practical part Tableau Tableau software does not require any technical or programming experience that I've already explained you earlier. Yeah, Tableau is user friendly. It is a great skill for data science applicable to any business fast and easy. Many of the things are getting repeated over here. I will skip this portion. Okay. Now what we'll do that before we go with this concept of data blending and other things. Now let me focus on the tableau. Okay. So if you have already downloaded the tableau and installed the tableau please open either you can open tableau desktop or tableau public or both also it's fine. So see when you open when you double click the tableau desktop you will get this kind of screen. Uh see this portion this portion here you'll not be able to see anything. Yeah, because these are the files which are already created by me. Yeah. So that's why yeah you can see that see these are some of the uh files which I which are which are created by my students in one of the university Indian university. So when I opened it uh yeah I can I can also click this this file directly and I can open this uh this tableau here. So initially in your in your case you'll not be able to see anything here. Now on the left hand side here you are having this area which is known as connect. Okay. So in the case of connect area you are having here Tableau server. So see in many of the big organizations what they do that they also purchase Tableau server. Yeah. In case of Tableau they are having two products here. Tableau server and Tableau uh online. Yeah. So suppose if I want to share my visualizations or if I want to share my Tableau file with my colleagues then I'm having two options here. Either I can purchase the uh Tableau online. Okay. Or I can purchase the Tableau server. Now if I'm working in a smaller organization, yeah, in smaller organizations the number of users will be very less. Let's say there are 10 people or 50 people let's say. So in that case I will not be able to go for Tableau server because Tableau server is very very expensive. I don't know the exact price over here but Tableau servers are very very expensive. So it is only useful for very very large organization. Yeah. Those organizations which are having some little bit of doubt about the security of their data. Yeah. and all those things for them. If they go for Tableau server then it is fine. Yeah, they can pay the money also and plus they they are having uh large number of users. So Tableau server they can buy it and then they can put all their visualizations all their data set on the Tableau server. Yeah. So if I want to connect to Tableau server I can click on it and then it will show me here the I have to write down the server name. name. I have to click on connect and then I have to give my username and password and then I can connect to the Tableau server. I can bring the data from the Tableau server. I can connect with the Tableau desktop and then I can start my visualization process here. Okay. So that is what we mean by the Tableau server here. Then we are having this portion here which is known as a to a file. So in the file we are having options like Microsoft Excel. If you're having a data set, let's say our majority of our data set are in Excel. So we'll be mostly using this button here known as Microsoft Excel. So if I click on Microsoft Excel, yeah, I'm just clicking on Microsoft Excel here. And now I can go to any of this file. I can bring the data from any of this Excel file. I can connect over here. Yeah, we'll also see further. Not now. I'm not showing you everything here just now. But I can connect any Excel file to Tableau by clicking this button. Then we are having text file. Either you say text file or CSV file. This is that option that we have to click. Then we are having JSON file, Microsoft X as PDF file. If you are having the data in PDF also you can connect that PDF file to Tableau and you can bring the data over here. Then spatial file I think. So spatial file is related to some geographical file I think. So I'm not uh yeah because I'm not using that file so much but yeah it is related to the geographical data and uh then we are having the statistical file. Statistical file here this is very very important option. See you must have heard about one tool one statistical tool which is known as SPSS I repeat SPSS. Yeah I have used that tool during my uh PhD work. So SPSS stands for statistical package for social science. Yeah, it's a tool from IBM and uh there you can do any kind of statistical analysis. Yeah, T test and F test and all those different kind of testing, hypothesis testing, yeah, regression analysis and correlation and all those things. So it's a very famous tool especially I know that in India it's very very famous and similar to that SPSS there is another tool which is known as SAS yeah SAS or yeah it's known yeah it is always spelled as SAS only so SAS is more famous in other countries yeah in India I'm not sure whether it is still famous but yeah SPSS in most of the universities I know that they use SPSS so suppose if you have created an SPSS file Now see SPSS is great for the statistical analysis but if you want to create visualizations then definitely you can use the tableau. So you can create a statistical file from your SPSS. Okay. And then you can connect that statistical file to Tableau by clicking this button over here. Yeah. So and I think so in PowerBI up till now what I know that in PowerBI you are not having this option to connect the SPSS file to PowerBI but in Tableau they are having this option. Yeah. Then we are having here more. More means if you if you are having something else let's say you are having XML file suppose XML your data is in XML file you can click on more and then you can connect to that particular file. Let's say XML file. Okay, you can connect over here. So these are the file options. Then come server options. So in the server we are having here Microsoft SQL server, MySQL, Oracle, Amazon Red Shift. These are the standard servers which we use. But apart from that we also have here more. Okay. So suppose if I click on more, you see here there are so many options here. These are installed connectors. So see there are lot of here Alibaba, Amazon, Athena, Azure. Yeah. Cloudera, datab bricks. Yeah. Drao, Dropbox. You see many many Google. So these are various options. If you click on this more here. Yeah. And also there are some additional connectors. Yeah. There are installed connectors are 71. Additional connectors are 38. These are very specific here. uh excess all denodo okay delta and many many more salesforce marketing cloud by tableau okay so there are many options here so when you click on more you get all these options here yeah so this is the Tableau desktop yeah these are the options which you get in Tableau desktop apart from that you also have here quick start okay what is this quick start here in the Quick start here it says jump start your analysis with pre-built template. So see in case of Excel also we have the templates. So if I want if I don't want to really create everything from scratch I I I I want to use some template then these templates are also available over here like Salesforce sales cloud okay budget controlling retail sales call center agent analytics you have to just connect your data with this file and then you can it will be done everything will be done. Okay. So if I click on view more, yeah, I have clicked on this view more here. And now here these are the various analysis which are already created. Yeah. Financial performance dashboard. Yeah. Salesforce data bricks. Yeah. See there are so many options here. It's a very very long list here. So you can also use this statistic uh this uh templates here. Yeah, you can use these templates over here, the ready uh the the built-in templates and you have to just connect the data and the visualizations are ready. So, this will save lot of your time. Yeah. Then there are these two sample workbooks. Okay. So, just like in if you remember that in case of PowerBI also we have one uh one sample data set button in the PowerBI if you remember. So, in case of Tableau also you are having these two data sets. One is known as superers store data set and another one is known as world indicator and plus here below it will show you the latest Tableau version. Yeah, if if you uh let's say if you're opening this tableau after 2 months suppose and in the in the next two months if one new version has come up then here it will show you that now you can download the so and so version. Okay. So here you'll be getting that information about the new version. Okay, definitely if you go to the Tableau desktop also there also you'd be getting that information but normally we we don't go to the Tableau desktop. Yeah, we we open this because today only I opened this Tableau desktop uh this tool and I saw that a new version was there. So I implemented I downloaded that new version here. Okay. So this is overview of that Tableau desktop. Let us let me show you here Tableau public. So this is Tableau public. Yeah, here it is already written Tableau public. See in Tableau desktop it will be written like this only Tableau book one. See in my case also I'm having currently the license version. So here it says Tableau license expires in 14 days because only I have installed and very soon I'll be also getting that free license for 1 year. So then I can uh yeah I can input that license code and I can get I can extend my license here. So this is when it is not written here any Tableau public then this is your Tableau desktop and now this is Tableau public. Yeah as I requested earlier that please also download this tool. Okay. Because if sometimes if the Tableau desktop is not working at least you can work with Tableau public for this particular training course I'm talking about. Here also you can see that see in the Tableau public you don't have that option of the Tableau server. So here in the Tableau public you are having all those options here. See here we don't have that option of Tableau server. You can see here there's no option of Tableau server. While in case of Tableau desktop I'm having that option. So see this is also one of the difference here. So these are the standard options here in the Tableau public. Excel text file, JSON file, Microsoft access, PDF, BL file, statistical file. Now see here if I'm having XML file, if I'm having the data in XML, I cannot connect over here with the Tableau public. I can connect only these seven files here. Yeah. Then to a server. In the server, I'm having option of O data and more. If I click on more, you see here in the Tableau public, I'm having only these three connectors. Only three. Okay. Google Drive, O data and web data connector. That's all. I've never used this web data connector. Yeah. And O data also. I mostly use the Google drive here. If I want to connect it over there. But now you see that now this is the first comparison here in the Tableau. This is my Tableau desktop. If I click on more here in the server, I see here how many? 71 + 38. Okay. So 109 connectors I'm having here. 109 in the Tableau desktop while in the Tableau public I'm having only three connectors here. So remember that Tableau public is only used for the training purpose nothing else. If you want to really use it in your organization you have to always go for the Tableau tester. Yeah, because no normally in companies we are mostly connecting the data from the Tableau say from the various server either it can be SQL server or Oracle server or IBM server. Yeah, we definitely we also use the Excel files and CSV files and all those things but here in that case of Tableau public I'm not having that option of connecting to SQL server or Oracle server or IBM server. Yeah. So this is one of the major limitation here between the Tableau in the Tableau public here. What the point? So what will what I was talking here that uh you have to we'll be connecting this file here sample superto204.xls you you already downloaded uh in one of the your folder. So we'll be connecting from the folder. Okay, we cannot connect from here from the LMS. It's not possible. So in this Excel uh Tableau desktop file, I'll be clicking on Microsoft Excel. Okay, I click on Microsoft Excel here. And now I have to go to that folder. Okay, so I go to that folder. Let me go to my D drive. Okay, simply learn Tableau course data files. And here I'm having that file sample supertore 2024. You can connect that sample supertore 2024 wherever it is available. I click on open. Yeah. And now here you are having the another window. You see here now it is a different window. When we were clicking on the Excel file Microsoft Excel, that was another window. Connect window. Yeah. And now when we when we already connected that uh connected that uh sample superstore 2024 data set with this tableau now you are getting this window. So here on the top area you can see sample supertore 2024 the file name it is written below Microsoft Excel. Now in this file you are having this three sheets here. Okay there are three sheets. So we are having order sheet, people sheet and return sheet. Now let me show you that file also Excel file. So in this data set uh I'll make it bigger. Okay. So in this data set we are having various uh first of all you can see below uh in my screen on my screen that we are having these three sheets over here. Order sheet uh people sheet and return sheet. Yeah. So there are these three sheets over here. The major sheet is the order sheet. Yeah. In most of our uh this practical part we'll be using the order sheet. But just now I want to also talk about these other two sheets also. But in the order sheet you are having here various orders. Okay. So we are having here first of all columns like row ID. Yeah. Row id you can see that it goes till what? How much? 20 uh 10,000. Yeah. The number of records are 10,194. Okay. So this is the number of records that you are having in this data set. Then we are having here order ID. Order ID as you can see that it is consisting of the country country code then year and this number. Okay. So this whole thing is your order ID here. Yeah. Then here uh yes it is containing the both the Canada uh data and the US data as I mentioned earlier. Okay. So this is US US US maybe in between also there is some Canada data here. Yeah. So yeah order ID. Okay. Then we are having order date, ship date. There are two dates over here. Order date and ship date here. Then we are having here the ship mode. So here if we see the ship mode then in the ship mode we are having four ship modes here first class, same day, second class and standard class. So four ship modes are over here. Yeah. So here we are having the customer uh ID. Then we are having the customer name. Okay. Customer name here it is combination of both first name and last name. Then we are having the segment here. Okay. segment we are having here three segments consumer segment corporate and home office then we are having here country as I said Canada and uh United States then we are having cities various cities yeah then postal code region now in region we are having here four regions central east south and west okay so there are four regions over here yeah then we are having the product uh ID. Okay. So this is the product ID here. Then we are having here category. Now this is important. Okay. So in our data we are having the three categories here. Furniture, office supplies and technology. And then after the category we are having here subcategories. So subcategories here if you count it should be 17. 1 2 3 4 5 6 7 8 9 10 10 11 12 13 14 15 16 17. Yeah. So there are 17 subcategories here. Accessories, appliances, blah blah blah. Okay. So here you can understand that there is a hierarchy. What is the hierarchy here? First of all, we are having on the top category. So there are three categories. Furniture, office, supplies and technology. Within the category we are having the subcategories. So you will see further in our visualization also we are having various subcategories. So under each category there are some subcategories and under each subcategory there are various products. Okay. So there are various product names. Here we are having the product name column the last uh one of the column here product name. So this is the hierarchy here. category then subcategory below sub below category we are having subcategory and below subcategory we are having the product. Okay. So this is what we are having here. Then finally after the product these are the various product names. Then f uh at the end we are having these four uh columns here four numerical columns sales quantity discount and profit. Yeah. So these are the four numerical columns that we are having here sales quantity discount and profit. Yeah. So that will be also using. So these are all the columns which are available in your uh this uh orders table here or order sheet here. Now we go to the people sheet here. Let me make it bigger for you. People sheet. In the people sheet I'm having here managers, regional managers and the region. Okay. So there are four regional managers for four regions here. Okay. Now see here this column region column in the people's table people's table or people sheet the region column is there west east central south and the same column is also available in your orders table I've already showed you the region column in the orders table here okay so just remember that this is the common column between the two tables here between the people's table and the orders table there is a common column which is known as region column. Just remember this point. So this is people's table. Then comes the returns table. Returns table or return sheet. Return sheet means in this returns table it is having the details about all those order ids which are returned by the customer because they are not happy with that product. As we know that in case of Amazon there is a 30-day uh return uh return policy. So here all these uh order ids okay all these orders which have been written by the customer their details are over here. So here there are only two columns in the returns table that is returned. Yeah everywhere it will be yes yes yes yes. Okay. So uh these are the return uh or say return column and the order ID column. Now see this order ID which is available in the returns table. The same order ID is also available in your orders table. Yeah, I already shown you this orders table. The order ID the second column here. So also remember the second point here that there is a common field between the orders table and the returns table and that common field is known as order ID. Yeah. So this is a common field and between the orders table and the people's table we are having the common field which is known as region field. Okay. So this is what I wanted to highlight here. I'll close this file. Don't save. Okay. So here on the left hand side now I'm back in the tableau. So on the left hand side here so on the left hand side here uh you can see these uh three sheets here. Okay. Three sheets here. Yeah, these are getting repeated here. Don't worry about that. But these are the three sheets here. Order sheet, people sheet, and return sheet. Yeah. Now, what it says here in the center area, it says drag tables here to create a data model. So, now I have to uh see, let's say I'm having here three sheets. Now, if I want to use here, let's say order sheet here as a data set, then I have to drag this order sheet and I have to place it over here in the center area. So now I'll request all of you to simply drag this order sheet with your mouse. Drag the order sheet and you drop it over here on this area. Okay. So drop this order sheet. Drag it and drop it over here. So see when you drop it over here in the middle area then you can see that now the order sheet is over here. Okay. And now here you can see the this is the table. Now see there are two tables over here. This table what you see on the left hand side here this table this is known as metadata. This table is known as metadata. Again I'm repeating what we have to done here. We have simply drag this order sheet and put it over here on the blank area. Okay. and then these things will come up here. So this first table it is known as metadata. What is metadata? Metadata in simple words it is data about data. So if I want to know that how many columns are there, what are their names and then from which table they have come up then this information is available over here in this metadata. So here we are having four columns in the metadata table that is type. What is this type over here? These are the data types here in PowerBI also you must have gone through the data types like text data type, date data type, time data type, whole number, decimal number, fixed decimal number. Yeah. So whatever the data types you have learned in PowerBI almost the similar data types are also available here in the Tableau. So this type means the data type column. Okay. We'll also see further this thing. Yeah. ABC I think so in PowerBI also you must have seen that ABC means the text data type here it is known as string data type the name is different in PowerBI it was known as uh text data type here it is known as string data type this ABG yeah while these are the icons of the date yeah because order date and ship date these are date so these are their icons and when you see this hashtag here hashtag means we are talking about the numbers now numbers can be both whole number and decimal number. Yeah. So this is this is the symbol or icon for the uh numerical field. Okay. Numerical field. It can be decimal or uh whole number but the icon is same here. Then we are having the globe icon here. Globe icon means these are the geographical field. In case of PowerBI also we have the geographical field which is which are identified by the globe icon. Yeah. So, country, public region, city, state, public, province, postal code. These are all the geographical field and these are already identified very well by Tableau. We don't have to do anything here. Now, at the bottom area, you can see there our four numerical fields as we have seen in the original data set also. Sales, quantity, discount and profit. Now, here also we have the hashtag. Okay. Now if you see that here the colors are green color. These four hashtags are having green color. While above if you see this row id yeah row ID is also a number. So it is having a blue hashtag. So see though it is a hashtag but it is identified it is shown in two different colors. One is blue another one is the green color. So what is this blue and green? That also we'll see further. Yeah because it is indicating something over here. Yeah, they have not just made it look beautiful. Yeah, it is having some purpose here of this green color and the blue color. So that we'll see further. So here we are able to see the type then the field name. These are the field names, row ID, order id blah blah blah. Then we have the table physical table. So currently what we have done we have drag only one table and the table name is order sheet or orders table. So here everywhere you will find orders orders orders. Suppose if we will also bring very soon this people's table and then here you'll be also finding the fields of the people's table and you'll be getting you'll be also able to see here the physical table in the physical table column that is the people's table or returns table if we have if we are bringing this table over here. Yeah. Then we are having here uh remote field. So there is another column here which is known as remote field. So see remote field name if you see if you compare the field name with the remote field name column they are exactly same here. Row ID, row ID, order ID, order ID, order date, order date. So now the question will come that why Tableau has given these different names over here? Why we are having these two separate columns? So if the field names are same then what is the logic here of giving these uh two columns here. Yeah. So that also we'll see now. So this is the metadata. Okay. Metadata table here where we can get a quick overview about our data set. Just now we don't require this metadata. So if you don't want to see this metadata table, you can click this icon here. This icon the arrow. I can click on it. And when I click on it now it is getting collapsed. Okay. See this is that button. So click click on it and it get uh the metadata table get collapsed. Now this is our main table. Okay. So in the main table we can see all these column that we saw in the original data set also. All the columns are available over here. Okay. And their icons are also available on the top. Yeah. The globe icons ABC. Yeah, that is the text data type. Okay, so this is the data set. Now just now here how many records are shown here? You can see the number of records or number of rows. How many it is showing you currently here? 100 rows only 100 rows. Okay. Now how many records we are actually having? More than 10,000. 10,100 something. Okay. 10,200 approximately we are having records or number of rows but here it is showing you only initial 100 rows. Yeah. So in case of PowerBI also if you remember that when we are connecting a data set and when we go to the power query editor window there also we can see the initial 1,000 rows not all records. Yeah. So if I want to do the data analysis here I I can see the see definitely all the records are connected to PowerBI but in case of PowerBI it will show you initial 1,000 rows but while here in the case of Tableau it is showing you initial 100 rows only. But suppose if I want to increase this number of rows yeah I can also write down here one more zero. I write down here one more zero and press enter or play or press this button. Now it is having around 1,000 rows. Yeah, if I go down here, you see here 1,000. Okay, row ID is 1,000. But I would say that you should not make it 1,000 rows. Keep it only 100. Okay? Don't don't worry that oh only 100 rows have come over here. No, no. All the 10,000 rows have come over here. But here for the visual for the view purpose it is showing you only 100 rows but I made it to 1,000. Now just now let me make it to uh let's say I can also write down here one more zero or let me write down here 11,000. Okay let's say I want to see 11,000 rows. Let us assume that I don't know how many number of rows are available in my data set. Yeah. So, I'm writing here let's say 11,000 rows. I press enter and see when I press enter here. When I press enter, it is showing me here this thing. Yeah, here it is showing me 21 fields and 10,194 rows. What is this fields? Fields means this number of columns. Either we say number of columns or number of fields. So here it is already showing me 21 fields or 21 columns and this many number of rows are available. So here it will show me the full number of rows numbers but when when it is showing me here below it is showing me initially 100 rows only. Yeah. So let me make it to here 100. Press enter. Okay. So now it should show me showing me here 100 rows. Okay, that is fine. So this is the data set. Okay, now so as I said that in case of Tableau, the Tableau desktop or Tableau public is not having all the features of data cleaning and data transformation just like PowerBI. Okay, here we are having a separate tool which is known as Tableau prep. Let me also show you a quick overview about the Tableau prep. This is the Tableau prep prep builder. Okay. And I think so maybe two to three months before I had created uh this kind of data cleaning here. Sample. So this is the super store data set. You see here. So see here I was having separate files. Yeah. These were separate files for south region, east region, west region, central region. Just now in the sample supertore data set all the data set all the all the files have come together. Okay. But uh suppose if you are having these kind of situation where you are getting the uh the orders uh data from various regions. So it will be different files. So I can bring those uh let me see if I can make it bigger for you. Oh I don't think so. No, I think so it is not. Maybe I have to check it. But here you can see that some of the files I brought over here. Okay, I connected with the Tableau prep. Then I did some uh cleaning here. Yeah. Some fixing some dates, renaming the states. Then I I combined this all these four files into one file. Yeah. So it was it is known as a data union here. We'll also talk about this data union in our Tableau desktop. And then I did some further cleaning here. I also added this returns table. You see here there's a separate returns table here. Okay. And that is how I'm doing this data cleaning in the Tableau prep. So this is a separate tool over here. Yeah. So this is what I wanted to show you here. Another uh Yeah, I can also make Yeah. And now I can make it here bigger here. Sorry. Okay. So see this is that uh cleaning which I have done here. So here you can do many things in the Tableau prep. But if I'm coming back to this Tableau desktop here, I show you some basic data cleaning which can be done over here in the Tableau desktop or Tableau public. So let's say uh I'm having this customer name over here. Okay, this is the customer name column. Now, first of all, if I click this ABC here, ABC means text data type. If I click this ABC, here I can see all the data types of uh Tableau. So, in the in the Tableau data type, we are having here decimal number, whole number. Yeah, just click this button. Any of this button. Okay. If I click this ABC button, I can see here decimal number, whole number, date and time, date, string. Yeah, here it is identified string. String mean check data type. Then spatial, boolean, booleans means true and false. Then it has identified as default. Then there are also some geographical fields here. Geographical role, image ro blah blah blah. Yeah. So here it is identified it as string data type that is a text data type. Now what I want to do here I want to create here two separate columns. I want to have one column of first name and one column of last name. I don't want to have a combined column here. So if I want to divide this one column into two columns or if I want to split this one column into two column that is possible here. What I have to do? I have to click this I have to click this drop down here. Okay. Click the drop-down here is a drop-own button in this customer name column. And then here when I click on the drop-down I'm having here options like rename, copy values, hide, aliases, uh create calculated field, create group, split, custom split and describe. Yeah. Now before I split, before I use the split option, let me show you what is this rename here. Rename that's very clear that you can rename this thing. But let's say I'll show you one example here. Rename. Yeah. Now I'm opening this metadata again. Metadata table because I want to explain here that why Tableau has given you these two separate columns here. Field name and remote field name. Though they are having exactly the same fields but why these two columns are created here. So now I'll show you one demo. So here in the let's say we are having here row id okay the the the original column name is row id now I want to change it to row number instead of row ID I want to change it to row number so what I'll do here just like tableau uh powerbi we can double click on that field name or column name so here also I can double click I double click on the row ID and now what I do instead of row ID I write down here row number. So see I have double click on this title row id and I have written here row number instead of row ID. Press enter. Press enter. And now here you can see it is now row number. I have changed the I have renamed it column. Now see here it is row number. And now you see the difference here. See field name. The first field name is shown as row number. But you see the remote field name it is still row ID. So now you have got that concept that why this tableau has given you two columns here because sometime if I change this uh column name then I should be knowing that what what was the original column name. Yeah. What was the original column name? So original column name will always be shown in the remote field name column. Yeah. You cannot change this one. You can change this one but you cannot change this one. Yeah. See I can double click over here. I can double click on the field name also here and I can change the name. But I think so here I cannot click. Yeah. Yeah. Here I cannot click on the remote field name. This will be permanent. Yeah. So that is the advantage that you get for the remote field name that you don't you lose your original column name. Tomorrow if you want to again go back to your original column name you can see okay uh it was row ID. So now you can again I can click on row number. I can again I can type here row ID. Row id press enter. And now you see it is row ID. Row id. Okay. So that is the advantage that you get here. Okay. So this was one demo here. Now let us come back to the customer name. Here in the customer name I want to split this customer name into two parts. Customer first name and customer last name. So what we do? We click this drop-down and in the drop-down there are two options here. Split and custom split. So let us understand what is the difference between split and custom split. First of all we'll go for split here. Split. Yeah. So click on the split button. After clicking on the drop-down in the customer name, click on the split button. When you click on the split button, what happens? Nothing happens. You see, you can see that oh Samu nothing else happened here. But now you go to the right hand side. Go on the extreme right of this table. Yeah, you can use this uh scroll bar. Go to the extreme right. And now here you'll be able to see these two columns here. Yeah, when you once you click on the split button in the customer name column, then you go on the extreme right of this table and here you'll be able to see customer name split one and customer name split two. Yeah, see these names are given by Tableau. We have not given any name. These games are given by Tableau. Now here if I want to change the title here because see customer name split one, customer name split 2 doesn't look good. What I can do? I can double click over here. Double click on the title and I can write down here customer first name and I can remove the split one. I don't like split one. So see I have changed the name here change the title of the column customer first name and similarly here I can double click and I can write down here customer last name and I can remove this split two press enter and see now my columns are ready. Yeah, in case of PowerBI also we have the split button. So I can divide the splitting uh in the split also we are having there seven options I think. So in case of PowerBI uh split by number and then split by uh characters and uh delimiters and all those things. Yeah, there are seven options which are there in PowerBI for the splitting the column. So here this is how we go for the normal split. Now see what this split has done that here the splitting has has been done when there is a space over here. Yeah. So here we are having this space between the two columns here sorry between the two names here. So it has done the splitting uh uh yeah when there is a space here. Okay. So that is how it has used this concept here. So this is the sorry these are the two separate columns and remember that the columns that you are creating here it will be always shown at the end. Okay so this is customers first name customer last name uh let me see uh maybe we can do it later on also. Now one important thing here you see that on the top area you can see this blue line here. Yeah there is a continuous blue line. Okay. While here on these two columns there is no blue line on the top. Yeah. Here there is a blue line. Here there is no blue line. So what does this blue line indicates? So blue line indicates that all these columns are coming from the original data set. They are coming from the original data set. That's why it is indicated by this top blue line. While these two columns have been created by us. Okay. So the columns which are created by us that is what you have also understood in this PowerBI the calculated uh column. Yeah. So these are your calculated columns. Yeah, here definitely I have not done I have not put up any function here. But still I have created this column on my own. That's why at any point of time if you are getting confused that which columns are created by me and which columns are coming from the original data set, you can use this blue line here. Blue line means the columns are coming from the original data set. When there is no blue line, it means that these columns are created by us. Whether it is created by splitting or whether it is created by calculated field or calculated column that's a separate thing. Okay. So that's why these are the two columns which are not having that blue line. So this is one splitting there's a normal split. Now another example custom split. Okay custom split. So suppose here if you come to this left hand side area if you click on this order ID. Now as I said earlier that order ID is consisting of three parts here. The country ID or country short form US or CA the year year and the last six digits here. Okay. So there are three parts over here. Now what I want to do that I want to create one column. Yeah. and I want to get only the initial two alphabets in that column. Okay, just now in this order id column I'm having all the three parts but I want to create one column where I want to see only the initial two digits US or CA. Okay. So if I want to extract only uh one portion of this uh whole series what I can do I can go to this order id click the drop-down here and in the drop-down I go to this custom split here. Okay I click on the custom split because if I go for split let us also try what is the split? If I click here split here. Yeah. So split I have used. Now let me go to the right hand side here. So see in the right hand side what has happened here it has now created here three columns for the order order id. I have used the split option. So order ID is split one order ID is split two and order ID is split three. So what it has done that wherever you are having the dash at that point the splitting has taken place. Yeah the splitting has taken place at the dash. Dash is your delimiter or space is also your delimiter. So it has done the splitting over here. But here we have got how many column? Three columns because there are two dash. Now suppose if I don't want to have all the three columns. I want to have only one portion that is this US or CA. What I can do here? I can come to this order ID. I click on the drop-down and in the drop-down I click this custom split. Okay. I the custom split. In the custom when I click on the custom split I'm having this dialog box what it says how should this data be split use the separator so here I have to tell Tableau that what kind of separator I'm having here so here we are having the separator that is dash so in the use the separator I have to put here dash I have to type here dash if you are having space you press space bar. If you are having comma, you you press here comma. So use the separator. I put here dash. Type here dash. Now here it says split off. In the split off, if I click the drop-down, split off, first, last and all. Now what is this first, last and all? So see here how many dash I'm having here. There are two two dash here. So now I can also tell tableau that where the splitting should take place. whether the splitting should take place at the first dash or first delimiter or the last delimiter or all delimiters. Yeah, the split off is talking about the where do you want to do the splitting at the first delimiter or last delimiter or all delimiters. So suppose if I go for first okay because I want to extract only this US and CA I I go for split off at first delimiter then it is asking me okay how many columns you require. Okay now see if I do the splitting here. Yeah let's say if I do the splitting here then I'll be having actually two columns. One column will contain the USCA and the other column will contain this another portion. Okay, one column will contain this USCA and the second column will contain this 2021-103800 0 because see here I have not done the splitting. I'm telling the Tableau that please split do the splitting at the first delimiter. So split off first. Okay. and I I and I want to get only this first column here. Okay, because I want to get only this US and CA. So I'll be saying here first one column. Okay, split of first and one column. I click on okay button. And when I click on okay button, now let me go to the uh right hand side extreme right. And you see now if you go to the extreme right we are having only one column here because see these three columns I created by using the simple split option but this column order ID split four this I created only with the custom split and I said that I want to see only one column. Yeah if I would have said here two columns then I would have seen here two columns. One column will contain USCA and the second column will contain 2021- something. Okay. But I said no no I want to go for only one column. So I can see only one column here. Yeah. So that is how you are using the custom split here. So you can tell Tableau that where do you want to have the splitting first uh delimiter or last delimiter or all delimiters and then finally how many columns you require whether you want to have one column or two column or three column. Yeah it all depends upon the column that we require. Okay. So I hope that this is clear. So here you can do these kind of simple data cleaning. You can uh rename the uh column names over here. You can do the splitting. Okay. Definitely you can also create here calculated field. Calculated field means calculated column. Okay. See here the names are different. In case of PowerB it is known as calculated column. While here in case of Tableau it is known as calculated field. Yeah, just the names are different but we'll be talking about this calculator field when the topic will come up. This group and beans also we'll be taking uh at the appropriate time. Yeah, aliases means different names here. Suppose if I click on aliases. Yeah, aliases. Let me do one thing. If I click here row ID and let me write down here row number row number and now if I click on drop-down and if I click on aliases yeah here there's no aliases here. Normally if see for aliases means I can I can give some name here. Let's say instead of this sheep mode in the ship mode I'm having the standard class but sometimes I people they also write down something else. instead of standard class it will be uh standard type let's say okay so if it is standard type instead of uh yeah that's a alias for standard class then I can see here that what kind of aliases are available here just now in this example there is no aliases aliases means different names okay for the same thing what are the different names even but here there is no aliases so it is currently blank yeah so we can do the splitting we can also hide the column here. Okay. So now uh first of all let us uh connect our sample supertore data set that we created that we had seen yesterday. So it's a excel file as we know. So we'll be clicking on Microsoft Excel and then I'll be selecting that file sample supertore 2024. Okay. Click on open. So in the customer name column as you know if you want to do the splitting we want to have first name and last name. So I can click on this drop-down over here in the customer name and I can click simply the split. Yeah because I don't want to go for any custom split. I want to go for split only. So I click on split and once we click on split for the customer name now we can go on the right hand side and here we can see those two columns that we have created. Okay. And I also showed you that we can here do the renaming. Then yesterday I we we also discussed about this blue line. So blue line I said that if you are if any column is having a blue line on the top it means that that column is already coming from the original data set. Okay. While these two columns are not having that blue line on the top. So it means that these two columns are created by us. Okay. they are not coming from the uh original data source. Now uh suppose if I want to delete these two columns. Yeah. So I can click on this uh I can select by pressing the shift button. Sorry control button. So please press the control button and you can select these two columns if you have created otherwise you can see over here. So press the control button and select these two columns. And now I can click any one of these drop-down. And when I click on the drop-down, you can see that I'm having here rename option, copy values, hide and delete. Okay, specifically I'm having this option of delete. Now I will not click here just now delete. But suppose if I click this option, this column let's say profit column. suppose okay I select the profit column I click on the drop-down now in the drop-down here in the profit column I do not see the delete column delete option here yeah I go for any column here suppose if I go for product name in the product name also if I click the drop-down I do not see the delete option I'm having only the hide option okay and plus other options are also there but there is only hide option there is no delete option here. So what does it mean? It means that whichever the columns are coming from the original data set, those columns cannot be deleted here. Okay. They will stay permanently over here. Definitely you can hide the column. Yeah. Suppose if you don't want to see let's say this category column suppose. Okay. I don't want to see the category column. So I can simply I cannot delete it. I can click on the drop-down. I can click on hide. Okay, I click on hide. So see now my category column is now hidden. Okay, but I cannot permanently delete it. What I can do here? I can delete only these two columns which are created by us. So I'll select this customer name split one. I'll press the control button and then I'll select the second column. So two columns I have selected by pressing the control button and then I click on one of this drop-down and I can click on delete. Okay. So these two columns I can delete. I click on delete and you see that now those two columns are gone. Okay. Customer name split one and customer name split 2 they are gone. Okay. Now here I have already hidden the category column. Okay. Now if I want to uh bring that column back. Okay, I don't want to hide that column category column. I want to bring that column back. So what I have to do, I have to click on this gear icon here. Okay, let me start my marker here. So I can click on this gear icon and I click on the gear icon here. You see here it is written show aliases and show hidden fields. Okay. So suppose if I click on this drop if I click on this uh gear icon and if I click on the show hidden fields if I click it then I can see here that my category column is now hidden but it is I'm still able to see that category column here. You see? And now if I want to unhide this column category column I can click on the drop-down here and in the drop-down I'm having the option of unhide unhide. Okay. So I click the dropdown I click on unhide and now you see the category column is now not hidden. Yeah. Now it is available here. Okay. So remember this important point that the columns which are coming from the original data set original data source they cannot be permanently deleted from the tableau in the tableau they can be hidden if you don't require that field you can hide that field but you cannot delete anything and the same concept is also there in case of powerbi if you know this thing in powerbi also whichever columns are coming from the original data source I cannot delete it yeah I can hide those columns Okay. Uh but I cannot delete those columns. Okay. I can uh and the columns which are created by me let's say in PowerBI also we are creating the calculated column. So those columns can be deleted by us. Yeah that is fine. But I cannot delete the original columns. So this is the concept of hide and unhide. Yeah. anytime if you're having any issue let me know. Now uh one more thing here that I want to show you now see here we are having the orders table. We have brought the orders table over here. Now yesterday I showed you the other two uh tables also that is the people sheet and the return sheet or people's table and the returns table. Now what I want to do that I want to bring these two tables also over here in this area. Okay. Now, if you remember yesterday, I showed you that there is a common field between the orders table and the people's table. Do you remember the common field between the orders table and the people's table? Yeah. So, there was a region column which was common between the orders table and the people's table. And now the second question is coming over here that what was the common field between the returns table and the orders table. There was also one common field between the returns table and the orders table. So uh order id. Okay. So now what we want to do that we want to bring these two tables also over here. And uh definitely because there is a common field. So there will be some kind of a join over here. Okay. We'll be connecting one table with another table with the help of a join. So what I'll suggest you that if you want to create a join then uh if you put your pointer over here okay when you put your pointer on the orders table what it says here logical table equal to orders and then it says here doubleclick this logical table to see its physical table. Okay. So it is telling us to double click this logical table to see its physical table. So remember that whenever you want to see the concept of join yeah between the two tables then you go for the physical table or you go to the physical layer. So what you have to do here in this orders table you have to double click just double click this orders table and when you double click the orders table now this you see that something has changed here. Yeah let me delete it again. Yeah, I'll I'll double click this orders table. And now it says here order is made of one table. Okay, now this is a physical table or physical layer. You can say something like that. Now orders is there. Okay, you double click on the orders table then it will show you like this. Now what I'll do, I will bring this people's table here. Okay, I'll bring the people's table here. And you see when you bring the people's table here first of all it says here drag table to union. Now I'll also today I'll also talk about this what is this union concept but I don't want to union. You bring this table over here the people table. Okay bring it on the right hand side of this orders table and then you drop it here. Okay drop it over here. When you drop over here, when you drop the people's table over here on the right hand side of this orders table, you see that now people's table is connected with the orders table like this. And this is your join. Okay. This is your join here. Yeah. So orders table is connected with the people's table. Yeah. And this is a join. Now if I click on this join. Yeah. Just click on this join. And when you click on the join, you can see that there are these four types of join. Inner join, left join, right join and full outer join. By default, it is showing you here inner join by default. Okay. So this is the inner join. Inner join means it is taking only the uh fields or rows. So it is taking only the records or rows which are common between both the tables. Now are you having the concept of uh or say do you know the concept of these joints because these joints also comes in uh PowerBI maybe uh you must have been taught the merging of the tables. Yeah, merging queries. So maybe during the merging queries these uh joints must have been discussed but just I want to check that whether you know this concept of these four kind of joints. Inner joint, left joint, right joint, full outer joint. Yeah, if you already know the concept then I I will not repeat that thing. But uh if you want I can also discuss this four kind of joints. Yeah, because this concept must have been taught in slide concept. Please discuss. Okay, no problem. So then let me go to this presentation here of simply learn. So you will also find this presentation with you. So let me uh yeah here in this presentation it is showing the same thing what I've discussed. Okay, you see here that in the orders table and the returns table, we have created this join and by default it is showing you this inner join and what is the common field here between the returns table and the orders table that is the order ID. Yeah, here it they have taken first of all the returns table. We took just now people's table but the concept is same. Yeah. So the uh this join has been created between the orders table and the returns table. And these are those four joins that we have also seen in our uh tableau. And the common field here is order ID, order ID. Now let us understand these uh joints here. Okay. So here they have given an example where there are two tables here. One is known as your left hand side table which is having the product sales. So there is a product ID, sales, number of records. Okay. And there is another table which is known as right hand side table which is having the product profit. So here also you are having product ID, profit and number of records. Okay. Now here which is the common field between the two tables that is the product ID. Okay. Product ID is the common field here. Otherwise if you see the sales yeah uh definitely the number of records we cannot keep it over here common field because this product ID product ID is a common field here. Now let us understand what is this left join. Okay. So what is left join that in the left join it will take all the values of the left hand side table or it will take all the records. I I would be very specific here that it will take all the records of the left hand side table and from the right hand side table it will take only those records which are common with the left hand side table. So let me show you the uh the diagram here. See this is the left hand side left join here in the left join you can see that the left hand side circle is full. Yeah. So when it is full it means that it is taking all the record of the left hand side table. And if you see the right hand side table or right hand side circle it is taking only the the records which are common between the two tables. So here in this presentation if I go for the left hand side if if I go for the left join then it will take all these records of the left hand side table. Yeah. And from the right hand side table it will take only those records which are common between the two tables. So which are the common product ID? You see here 6 7 8 9 10. Here also we have 6 7 8 9 10. So from the right hand table on it will only take these five records. But from the left hand side table it will take all these records whether they are matching or not matching it doesn't matter. So this is known as left join because we are taking all the record from the left hand side. Yeah. Then comes right join. Right join is just opposite to left join. In the right hand side join it is taking all the record from the right hand side table and from the left hand side table it is only taking those records which are matching with the right hand side table. So here also the records which are matching are 6 7 8 9 10. Yeah. Here also you have 6 7 8 9 10. But from the right hand side table it will take all the record whether they are matching or not matching it doesn't matter. But from the left hand side table it will take only those records which are matching with the right hand side table. So this is known as right join. Then comes inner join. What is the inner join here in our table? If you see the inner join here. So inner join means it is taking only the matching record here. Yeah this is inner join. This is your inner join. Matching records. So here in the presentation if you go for the inner join then it says here the result of the inner join will include common data present in both data set. So the records which are common between both the tables only those records will be taken. So here records like uh product ID 6 7 8 9 10 here also we have 6 7 8 9 10 they are common. So only this five records from the left hand side table and five records from the right hand side table will be taken which are common. This is known as inner join. Okay. And the last one is very very simple full outer join. Yeah. When you see the diagram also here if you see the diagram of full outer join it is both the circles are blue. Yeah. So what does it mean that it is taking all the record from both the tables whether they are matching or not matching it doesn't care. So it is taking all the record from the left hand side table all the record from the right hand side table and that is known as full outer joint. In case of PowerBI just to give you an uh uh the differences here in case of PowerBI there are two more joints left entrains here. In case of Tableau we are having only four. So suppose if I want to uh tell you what is left anti-join. Left anti- join means that it will take only those records from the left hand side table which are not matching with the right hand side table. I repeat in the left NTA it says here that it will take all the record from the left hand side table which are not matching with the right hand side table. So which are not matching here the matching records are 11 12 13 14 15. Yeah these five records are not available on the right hand side. So when I go for left anti- join then it will take only these five records 11 12 13 14 15. Yeah only these records will be taken from the left hand side table but from the right hand side table it will not take any record. It will not take any record. This is known as left ent. Left ent. And the another concept in PowerBI is known as right ent. Right ent is just opposite to left ent. What is right ent? Right ent will take only those records from the right hand side table which are not matching with the left hand side table. So here you can see that these five records 1 2 3 4 5 product ID. These five records are not available over here. Yeah, they are not matching. So when you go for write entity then it will take only Yeah, it is known as write sorry for my handwriting. I'm writing by mouse write ent. Okay. So what is right entity here? Right ent means it will take this those records from the right hand side table which are not matching with the left hand side table and from the left hand side table it will not take any record. It will take only from the right hand side table and that is known as right entity. Yeah this is just for your information. Yeah. But in case of Tableau, we have only these four kind of join. Inner joint, left joint, right join and full outer joint. Okay. Good. So what we'll do here? You can decide whether you want to go for inner join or left ant or right ent or full uh full outer join. See it all depend. See whatever the join you select here accordingly you will see here that the number of rows uh number of rows will increase or decrease. Let me show you here. If I go for inner join you see here if I go for inner join then the number of fields are 23. Now why there are 23? Because initially out orders table was only having 21 fields 21 columns but now it is showing you showing you 23 fields. Why? Because there are two fields which are coming from the people's table. How many columns are there in the people's table? Two columns are there. That is the manager column and the uh another column is the region column. See here you can see if you go on the right hand side here extreme right hand side you can see here these are the two columns which are coming from the people's table. You see here the people's table. So regional manager and region bracket people. You see how it is written here. Region bracket people in the original table. It is not written region bracket people. It is simple written people in the original table the Excel table. But here it is showing you read regional manager and region bracket people. Why region bracket people? Because first of all you remember that two columns cannot have the same name. Yeah, in the data set two columns cannot have the same name. So here we are already having the people column. So region column here region column we are having in the orders table. So here in this column which is coming from the people's table I cannot write here simply region. It will be written like this only region bracket people. So it is showing us that this region column is coming from the people's table. Though above also it is written here people but this is how it is written. Yeah. So two columns are coming from the people's table and there are already 21 columns from the orders table. That's why you can see that the 23 fields are available. Currently what is the number of rows? 10,194 rows. Okay. Now suppose if I select here left join. Currently it is inner join. If I click here left join. In the left join also the number of rows are same. Let me click here. Right join. Right join also same and full outer will also be same. Okay. So it doesn't matter here. But in other example you will see further. Let us see with other thing. So just now what we are doing we are going let's say for the inner join just for the example purpose. Yeah you can also close this one. So orders table is now connected with the people's table. Now what we'll do? We will bring this returns table. Okay. This returns table also we bring it over here. And we drop it somewhere over here. Okay. We drop it somewhere over here. So now when you bring the returns table here, returns table is also connected with the orders table. And you see here as soon as the return table is connected with the orders table what kind of join it is creating it is inner join. Okay it is inner join by default it is inner join. So this is showing you the common field. Yeah when you click on this uh vend diagram you can see here order ID. Order ID. This is the common field between the orders table and the returns table. That's fine. But here just now by default it is inner join. And now you see here the number of rows see it has drastically reduced. See number of fields are 25. Now why there are 25? Because two fields have come from the returns table. If you go on the right hand side go on the extreme right you can see that these two columns return column and the order ID column are coming from the returns table. So that's why now we are having total 25 fields 21 + 2 + 2. So 25 fields are there total in now this whole table. Yeah. And the number of rows are very very low now. 3,226 rows. It is just one/ird. Initially how many rows we were having here? 10,100 something. Now if I want to increase this number of rows yeah I can go over here in this returns when diagram this uh join and what I'll do I will go for left join here instead of inner join let me go for left join okay once you click on the left join then you will see here that the number of rows will increase so let us click here left join and you see now when we click on left join Now the number of rows have increased 12,620 rows. Let us see what happens with the right join. If I click on right join, right join it is same 3,226. And if I go for full outer, full outer also it is 12,620. So I would suggest you let us go for left join here for this second thing. Left join. Okay. So the number of rows have increased. Okay. Instead of 10,000 something now we are having 12,000 something. Good. So this is how we can do the we can uh join the various tables with this table. See joins are uh dependent on what kind of analysis you want to do. Okay. If you say that I don't want to uh let's say I want to focus only on those kind of data which are common between both the tables then you go for the inner join but if you say because see this orders table I feel that this orders table is having all uh the majority of the records okay so normally it is suggested normally I'm using the word normally it is suggested that we people they go for the left join Yeah, if your orders table is your fact table, then you go for the left joint. So you take all the record because see you don't want to miss those records of the fact table. You want to take all the records of the fact table. So you normally you go for the left join but sometimes it happens it it all depends upon the the use case that if you say that no no I want to focus only on those data set which are common between the both the tables. I want to only focus on those order ID which are common between the returns table and the orders table then you can go for here inner join. Yeah. Now here if you we have done the joining. Okay. Now if I go on the right hand side extreme right. Yeah. You see here that in the returns table. Yeah return table. Initially you will see here null null null because there are some records uh yeah there are some order ids which are not available in the returns table but they are available in the orders table. I repeat here if you go to the extreme right you will see here null null null in the returned column and the order ID of the returns table. Why? because there are some order ids here which are not available in your returns table but they are available in your orders table. Now how it is possible? How it is possible that there are some order ids which are available in the orders table but they are not available in the returns table. items which are uh let's say uh which are order definitely yeah all all orders are not written okay because uh definitely the customers are happy with the orders so they would not like to return okay but return uh remember that I I I saw one story uh it was real story that uh there was a group of four or five people I don't want to name them I don't want to name the country also but uh they had done a big scam of just they earned the money uh uh based on the returning of the product. They actually never returned any product but they showcased that they had returned the product to XY Z company and the company had paid the money. Yeah. But actually after two two to three years the company realized that something was wrong. Okay. And there was a huge amount which they had earned out of that. Yeah. So there are very very smart people in this world who can do this kind of activity. Okay. That uh because what happen that let's say if we are talking about Amazon, Amazon is uh they are sending the product but the returning of the product is taken care of by another company and sometimes there is no communication between that uh the third party and this Amazon. So Amazon feel that okay this person has written the product but the the third party has not received that product and Amazon is paying some money. So something like that. So something is happening over there. So many people they have uh or some of the people not many people but some of the people they have misused this system and they were earning money out of that. Okay definitely we should not be going for that but uh yeah so definitely there are products which are not returned. Yeah not all products are returned. So that's why definitely here we are having this null null null. Now uh see here we can see that first of all we are having all the columns of the orders table and then we are having these two columns of people's table and then we are having the two columns of the returns table. Yeah. Now let us click on this gear icon. Yeah. Just click on this gear icon again. If you click on the gear icon, yeah, today also I'll show you this aliases, how to create the aliases and what is the use of these aliases. But we have already seen this show hidden fields. Yeah, because we had uh hidden one field and we have we want to uh we wanted to unhide. So we already know this hidden fields. Now we focus on this area sort fields. So if I if you want to do the sorting here just here only in this table in this uh window if you want to do the sorting of the fields then by default the sorting is done in uh uh uh the sorting is based on the data source order data source your original source your excel file. So whatever the uh the sorting is there in the original source the same sorting is also over over here. Yeah. So that is what we mean by the data source order. But suppose if you want to go for let's say ascending, you want to have all the fields in ascending order. So we can click on this A to Z ascending. Okay. I can click here A to Z ascending. And now what happens here when you click on A to Z ascending. You see here it is starting from category, city, country, oblique, region, customer ID, customer name blah blah blah. Then comes here order ID. You see here order date, order id and then this other order id is also available over here because they are sorted in ascending order. So this order id is coming from the orders table and this order ID is coming from the returns table. Yeah. So these two order ids are together. Then the region column you see the region column the two region columns one from orders table from one from the people's table they are also shown together. And finally which is the last column here in the ascending order subcategory of the last column. Okay. So it starts with category column and it ends with the subcategory column. So so this is your if you click on the gear icon this is your A to Z ascending. Similarly if you click on Z to A descending. Now if you click on Z2 descending definitely subcategory will be shown first just reverse and the category will be shown at the bottom. If you click the gear icon again then the next option here is A to Z ascending per table. Now what is the difference between A to Z ascending and A to Z ascending per table. You see when you go for A to Z ascending what it will do if you are having here three tables and whatever the number of columns you are having all the columns will be sorted together if you go for A to Z ascending or A to or Z to A descending but when you want to do the sorting per table let's say you are having orders table orders table is having 21 columns or 21 fields you want to do the sorting only of the orders table then you want to do the sorting of the people's table and you want to do the sorting of the returns table. If you want to do the sorting individually per table, then we we can go for this option. Let's say A to Z ascending per table. If I click it. So now here in A to Z ascending per table, it starts with category and it ends over here with subcategory. Okay. So this is your orders table. Then comes the people's table. In the papers table also first of all we are having region and then regional manager and then we are having the returns table. In the returns table also we are having here order ID and then return. Yeah. So here it is A to Z ascending per table. And similarly we can go for Z to A descending per table. But what I'll tell you here don't change any of these sorting fields. You go with the default one data source order. I'll tell you why why why this is not important. Yeah. I let's click again here data source order. This option data source order. Okay. Why this option is not that much important. Yeah. Just now see when you are focusing only on this area then you can go with this options that is fine. But now what we'll do that once we have connected these three tables with each other. Yeah. Now let us go to the uh we go to the visualization area. Okay. So how to go to the visualization area? You can see here at the bottom area. Yeah. Here on the uh bottom left corner here it is written here sheet one. Yeah. Below. Okay. And what it says here go to worksheet. Okay. So now if you want to start creating the visualization because we have done we have connected the data set here we have we have done the joining here. Yeah. Now we want to start the uh data visualization. Yeah. Yesterday we saw that there is not that much of data cleaning to be done in this Tableau desktop or Tableau uh public. The major cleaning can be done in the Tableau prep but that's a separate tool. So now we want to start with the visualization process. So what we'll do we will click here below left hand side bottom area sheet one I I click on sheet one and when I click on sheet one now we are in another window you see here this is another window and in this window you can see that now on the left hand side we are having this data panel okay now just you compare it with powerbi In case of PowerBI, in case of PowerBI you are having the data panel on the right hand side while in case of Excel uh sorry this Tableau you are having the data panel on the left hand side that's the difference okay this is one of the difference you remember this differences as I said yesterday that this this can be asked in interview if you're appearing for anything yeah so this is the data panel Now here there is also some difference here if we compare with PowerBI. See in PowerBI what happen that whatever the fields which we are having whether it is numerical field or whether it is categorical field or whether it is geographical field all the fields are shown together in power way and all the fields are shown in ascending order. Yeah it shows it always start with the alphabet A and then it ends with zed. Okay. So it shows in the uh ascending order but all the different types of fields are shown together. Now here in this tableau what happens you see here first of all we are having the orders table. In the orders table it starts with category it ends with subcategory. These are all the fields which are coming from the orders table. Then we are having the people's table. So these are the two fields of the people's table that we have already seen. Returns table is has also having these two fields. Now you see here again below it is showing you again below orders table. Here also there is orders table. Here also below there is orders table. Yeah. And in the orders table here it is showing you here discount, profit, quantity and sales. Yeah. So what is doing here in case of Tableau that all your numerical fields are shown separately here they are not mixed up they are not mixed up with these other fields while in case of PowerBI all the fields are mixed up but in case of Tableau this uh this four numerical fields which we are having here discount profit quantity and sales yeah they are shown separately suppose if your people's table and the returns table is also having some numerical field then they will be also shown over here separately. Yeah. So in case of now Tableau now the concept comes over here very very important concept in case of Tableau let me show you one concept here. Yeah. So in case of Tableau we are having one con two concepts here. one is known as dimensions and another one is known as measures. Okay. So, dimensions and measures. So, what is this dimension and what is this measure? Yeah. So, here it says dimensions contain Yeah. Dimensions contain qualitative values. Just remember the word dimensions means qualitative values. and measures means quantitative values. So dimensions contain qualitative values such as names, dates or geographical data. Yeah. So here in our example if you see the data set we are having here city, category. Yeah. Even customer name, order date, order ID, postal code. These are all qualitative data. Okay. product ID. Yes, you can see here that product ID but our product ID is combination of some text, some year and some numbers. Okay, but if I focus on let's say categories. So we saw yesterday the three categories office supplies, technology and furniture. So whenever you are having these different categories okay or different customer names will be different okay the ship mode is different there we there are various kind of ship mode like same day first class second class yeah likewise then ship dates are also different. So whenever you are having these kind of fields they are known as dimensions. They are known as dimensions. And if you are talking about the numerical field, let's say these are your four numerical field, discount, profit, quantity and sales. They are known as measures. Okay. So you have to remember these two words here. Uh here that is dimensions and measures. What are measures? Measures contain numeric quantitative values that you can measure. Measures are aggregated by default. Aggregated by default means we will see further that if I take the sales value, if I take the sales field, it will be doing the summation. Yeah, in case of PowerBI also you saw that when we are taking the any numerical field, it will by default do the aggregation sum. Okay, it will sum all the sales, it will sum all the discount, it will sum all the profit that is the default characteristic of a numerical value. So here also our measures when we use the measure in the visualization it will do the aggregation. Yeah we we'll see today only. Yeah. What is dimension? Dimension means you remember the example of dates names categories. Yeah. Geographical data like city. Yeah. Country. These are all the examples of dimensions. Okay. Now if you focus on this right hand side area you see that this area this area okay these are all your dimensions okay and if you see the color of this data type or this icon here the color of these icons are blue color yeah they are all blue color here the icons I'm talking about while if you focus on this area. Okay, you see the color of this data type, color of this icon, they are green color. So what is this blue color and what is this green color here? Okay, so now we'll discuss this point here. Yeah, because they are identified separately here. Okay. So if if if you want to understand this blue color and green color then let us come back to this area. Yeah, this is see this is the if you want to have this article I can put it over here in the chat panel. Yeah, so that you can refer it later on. So here it says blue versus green fields. Yeah, that is what we want to discuss now. Tableau represents data differently in the view depending on whether the field is discrete or continuous. Now there are two more words here. Initially we saw this dimensions and measures. So dimension is having qualitative value and measures is having quantitative value. Okay. While here continuous and discrete dimension and measures they are very clear. But now comes here continuous and discrete. These two words also they are that also you have to remember. What is continuous? Continuous means here it says continuous means forming an unbroken hole without interruption. These fields are colored green. When a continuous field is put on the rows or column shelf, an axis is created in the view. Yeah. First of all, let us read this line and then I'll explain. Discrete. Discrete means individually separate and distinct. These fields are colored blue. when a discrete field is put on the rows or column shelf, a header is created in the view. So in simple words, if I want to explain you what is discrete and what is continuous, discrete means you're talking about the customer name, let's say. Okay. So customer names will be separate is discrete. Okay. If you talk about uh categories, subcategories, uh ship mode, they are all discrete. Yeah. uh one category will be totally different from the other category. So that is known as discrete while continuous example will be let's say temperature. Okay. Example is temperature. Temperature will be let's say it will be 10.1 10.2 10.3 10.4 10.5. Yeah. And so on then it will be 11.1 11.2 11.0. So it's a continuous value. If we talk about pressure, pressure whatever the value of the pressure will be there that will be also continuous value. Okay. If I'm talking about the marks also marks of the uh marks in the exam they are also continuous. Okay. So normally you remember like this that whichever fields which are having numbers they are by default continuous. Whichever fields are having numbers they are by default known as continuous field. So normally all your measures all your measures are by default continuous because measures are containing the numerical field numerical value. So by default measures will be continuous and by default dimensions yeah dimensions will be by default discrete because dimensions I gave you that example here names dates geographical data yeah they are all separate they are all separate from each other so they are by default discrete okay so remember like this that dimensions are by default discrete measures are by default continuous. Okay, by default you use that you uh remember that word by default but but here we can see that discrete dimension and continuous dimension. Now see I said that dimensions are by I by are are by default discrete but here it is also showing you one example where dimensions are also continuous. Okay. So I can convert remember one sentence. I'll also show you practically that dimensions which are discrete by default. I can also make it continuous. See here you can see this order date. What is order date? Date is a discrete value. It's a me it's a dimension. So normally the date will be discrete because it's a dimension. But I can also convert the same date into a continuous dimension. Yeah. But I'll show you this thing practically in the tableau. Now measures measures are by default continuous. So here we can see sum of profit. This is a continuous measure. But a measure can also be discrete. A measure can also be converted into discrete value. So that also we'll say practically. Okay. So a dimension will be by default discrete. But a dimension can also be converted from discrete to continuous. And when the dimension is converted from discrete to continuous, what is the discrete dimension? Discrete dimension is always shown in blue color. But as soon as you convert that dimension into continuous value, you see here the color is now green color. Okay? And when the measure is continuous by default the measure color will be green color. But when you convert that measure from continuous to disc create the color will change from green color to blue color. So I would say that I I can think that it will not be so easy to understand this concept but once we'll go for the practical part now then you'll understand this concept. Okay. But at least you remember these four words dimensions, measures, discrete and continuous. Yeah, just take these words here. Okay, discrete means they are separate. Okay, while continuous means it's a continuous value. Okay. And as I said that dimensions are by default discrete and measures are by default continuous. But a dimension can also be converted to continuous value and a measure can also be converted into discrete value. And these are the examples over here. Yeah. But you can check this uh this uh link also which I have shared over here. Yeah. Okay. Good. So now let us come back over here with this theory part. So here you can see that all these dimensions yeah which are by default discrete so they are shown in blue color and they are shown separately here while the measures are shown separately and measures are by default continuous so they are shown in green color. Okay so this is just the difference between the powerbi and tableau. Yeah. Now here we can see that this is your canvas. Okay, in this canvas we'll be creating the visualization. Then above here we are having these two blocks on the top area. These two blocks are columns and rows. Okay. So columns means you can say x-axis and rows will be your y-axis. Yeah. Normally in case of powerbi we use uh don't use columns and rows. we use their x-axis and y-axis. Okay. So you can understand that these columns is x-axis and rows is y-axis. Then we have here uh these blocks are there. We will see also see one by one pages. Then we are having filter block or filter panel. Then we are having this marks card. Okay. These are the various panels that we are having here. We'll be using it one by one. And then if you click this one, this one here on the top right corner, it is written here, show me. Yeah, here. Top right corner, show me. If you click this show me, when you click the show me here, then here you are able to see the standard visualizations. Okay, when you see here show me, if you click on show me, you can see here this is your text table. You see when I put my pointer here on the first visualization below it is showing me that name. So when I put over here it says text table one or more dimensions one or more measures. So what it is showing here it is showing you the name of the u name of the chart and plus it is also showing you that how many fields you require and what kind of fields you require to create that uh measure or sorry to create that chart. So suppose if I put my pointer here on this first chart it says text table for creating a text table you require minimum one dimension one measure minimum okay that is what it is saying if you are having more it is fine but minimum for text table you require one dimension and one measure then this is your heat map heat map also require one or more dimensions and one or two measures likewise this is highlight table so we'll create one by one all these visualizations today or maybe in in the next session also. So we'll see this various types of visualization here. Okay. So this is known as show me and if you don't want to see this show me you have to click this show me again click on the title show me and it will get collapsed. Okay so these are the things. Now what we'll do let us create our first visualization. Yeah. So here on the left hand side we are having this category. So what I'll do that I want to see the total sales of various categories and I want to know that which category is having the highest sales which category is having the lowest sales. Yeah. So I want to focus on the category. So what we have to do if you want to create a chart what we do we drag this category. Now see when you drag the category here you see here just focus on this line. Sorry this one. Okay just focus over here. Let me draw it again. Okay. See you can see that there is a thin line over here. So what is this thin line here? This thin line is bifurcating the dimensions from the measures. Yeah. Because below this thin line all these are measures and above the thin line these are all the dimensions. Yeah. Now before I forget one thing uh you see here that in this in the dimension area you can see this measure names. Okay, there's one dimension which is known as measure names. And there are these four measures. You see these four measures. What is written here? Latitude generated, longitude generated, orders, bracket count and measure values. Now see these five things which we are having here, five fields which are shown over here, they are not in our original data set. Yeah, you have never seen these kind of fields in your original data set. Now see if you want to go to the original data set, what you have to do? If you want to see that table, sorry, mean your table. Yeah, just now what we connected that uh returns table with the orders table and the people's table with the orders table. Yeah, that join. If you want to go back to that page, what you have to do? You have to click this one. Just click this data source. Okay, bottom right, bottom left corner here. You click on the data source and when you click on the data source you are back over here. Okay. I can also double click this orders table and when I double click the orders table I can see this join. Okay. So just click on this data source when you are in the sheet. Yeah. So here you can see that in the in the data source when I see all these fields here I do not see here latitude, longitude, measure names, measure values. We are not having these kind of columns here. There are no columns like this in our data set. But if I go back to the sheet one, yeah, just click on sheet one. And now here these five fields are available. So remember that these five fields are generated by Tableau automatically. Whenever you are connecting any data set to Tableau, Tableau will automatically generate these five fields here. Measure names, latitude, longitude, orders, bracket count, and measure values. And we do not have here any control. Okay, I cannot stop this process. One more thing that this longitude and latitude these two fields we will only see in that data set which is having only which is having at least one geographical field. I repeat my sentence that this latitude and longitude field will be automatically generated by Tableau only when your original data set is having at least one geographical field. So here in our case what are the geographical field you see here city it is having a globe icon country is having a globe icon postal code is also having globe icon and the state public province is also having globe icon. So here in our case we are having four nu uh four geographical field. So definitely this latitude and longitude fields will be generated automatically by Tableau. But let us assume let us assume that in our data set we don't have any of these geographical field. Let us assume like that. So when you don't have any of the geographical field in your original data set then Tableau will never create these two fields latitude and longitude. Yeah. Then Tableau will create only three fields measure names count and measure values that's all. But if your data set is containing at least one geographical field it can be country, region, city. Yeah. Uh normally region is not counted as geographical field but country, state, city, postal code. Yeah. Uh so these are all the geographical field. So if if if your data set is containing one geographical field, minimum one geographical field, then automatically this latitude and longitude uh columns will be generated by Tableau. You don't have any control over here. Clear? And also these measure names and measure values and these orders count they are also having its importance. Yeah these three fields measure names count and measure values they are not just generated uh uh just for fun by tableau. It is having its own importance. So that also we'll see further clear. So now let us create our first visualization. So as I said earlier that we'll be dragging this category and you see when you are dragging the category here I was talking about this line here. Yeah. When I focus when I drag this field. Yeah. Just focus on this area. So what it is showing me here? It is showing me here the two words dimensions and measures. Below that line. Yeah. Near that line we can see the dimension. I remember that in the older versions of Tableau. Yeah. Because I'm also using this Tableau tool for last seven or eight years. I I learned this Tableau uh when I was doing my masters in data science from Bolognia University in Italy. Yeah. So there this Tableau was part of our course. So there I learned this Tableau. So during those days we were having the uh the uh or say the version that we were having in those days here in in in those days the in those versions it was clearly mentioned here on the top area dimension and here it was below mentioned measure but now they are not mentioning over like this. Yeah. So whenever I drag the field you see here below that line. Yeah. Just focus on this one area. Yeah. Now it is not showing me but yeah again I drag it. So now it is below it is showing me dimension and measure. So I drag this category I put it here in the columns area. Yeah I drop it over here in the columns area. So see now this category when it's dropped over here I can see these three categories. Okay. Furniture, office supplies and technology. Now what I require here in the row section I require a numerical field. Minimum one numerical field in the row section. So what I do I click here I I select here sales let us select here sales and I drop it over here in the row section. So see when I drag the sales and when I put it over here in the row section what it does here it does the aggregation. It is doing the aggregation. Yeah because it's a measure. Measure is always doing the aggregation. It's a continuous value. See measure are by default continuous. So they are shown in green color. This is a capsule. Yeah. And the category is a discrete value. So it is shown in blue color. And now you can see as soon as you drag the sales here. Yeah. We can it is doing the sum of sales by default. And now I can see the chart. This is a column chart. Yeah. This is a simple column chart. Now see here this column chart is ready. But you see that here we are having lot of blank space. Yeah, there is a lot of blank space here. Now remember one thing yesterday I told you that in the case of PowerBI as you know that in PowerBI on one page I can create many visualizations. Yeah, in the PowerBI desktop I'm talking about on one particular page I can create five visualizations. I can create 10 visualizations also. In case of Tableau here you see the name below what is written here sheet one. So in Tableau we are having various sheets. Sheet one, sheet 2, sheet three, sheet four. Just like Excel in Tableau in one sheet I can create only one visualization here. In this sheet yeah you can yeah you will suggest me that okay Samir here also we can create another visualization. No it is not possible. Yeah, I cannot create here another visualization in this one sheet because this visualization is already created by me. So this is the difference here between the Tableau and PowerBI in Tableau in one page or one sheet I can create only one visualization. So now what we have to do we have to utilize this empty space because it doesn't look good. So to utilize this empty space what we can do we can click on this dropdown here. You see on the top area this drop-down. Yeah. If I click on this drop-down, I can see here four options. Standard, fit width, fit height and entire view. Click this dropdown. So by default it is standard. By default it is standard. Now if I click on fit width. Yeah, just click on fit width. So what happens when you click on this fit width? It is expanding horizontally. Okay. Okay. So now this is looking good that it has occupied the whole area. So this is fit width. What is fit height? Feet height means it will go vertically. It will expand vertically. But what is my suggestion to all of you that sometimes what happens that if you are using feet width so it will expand vertically. It will expand horizontally but it will not expand vertically. If I click on fit height it will expand vertically but it will not expand horizontally. So what is my suggestion to everybody that don't use your brain? Simply click on entire view. What is entire view? When I click on entire view, entire view will expand horizontally also. It will expand vertically also. Yeah, in some of the scenarios you will see this thing that when I when I click on fit width, it will expand vertic uh horizontally but below you'll be having some space. So it will not expand vertically. it will expand horizontally only if you go for fit width. So what I do always when I am having here standard instead of standard I simply select here entire view. So it will expand in both the direction vertically and horizontally. Yeah. So every time I'll be telling you please make it entire view. So you have to come over here to this drop-down and you have to click this entire view. And now it is done. Okay, good. So this is what is your Yeah, here we have created the whole page. Okay, whole sheet. Now if you see the sorting here, see how the sorting of this column is done. It is written here furniture. The first column first block is of first column is of furniture then office supplies and then technology. So here the sorting is done. How the sorting is done? The sorting is done in the ascending order of the category. So first of all it starts with furniture then O and then T. So sorting is done. But now what I want to do I want to do the sorting of these columns based on the sales. I want to see the category which is having the highest sales I want to see it first and the category which is having the lowest sales I want to see at the last. Okay. So I want to sort these columns in the descending order based on the sales. I don't want to do the sorting based on the name of the category. I want to do the sorting of these columns based on the sales and that and that too I want to do it in the descending order based on the sales value. So how we can do the sorting? So say sorting can be done in various ways. So I'll show you one of the way here. You see here when I put my pointer on this sales column. Yeah. The sales title. There is one small button over here above the sales word. Yeah. Can you see this button here? Yeah. So we have to click this button. This is the sorting button. Just put your pointer above the sales. put your pointer on the sales and then you will see this button. See, as such, I'll not see this button. But when I put my pointer on the sales, this button will appear. I click on this button. When I click on this button for the first time, you see the sorting is done. Now, the sorting is based on the sales. Yeah, we can see that technology is having the highest sales followed by furniture and then followed by office supplies. If I want to do the sorting in the ascending order, in the ascending order based on the sales, I have to click this same button again. Yeah, this button again. I click it. And now you can see it is doing the sorting in the ascending order based on the sales. And again, again if I click this same button third time, okay, third time I click it, then now it is doing the sorting. But it is now doing the sorting based on the category name. See again we are having furniture, office supplies and technology. Okay. So this button is used for sorting. When I click the button for the first time, it is doing the descending sorting based on the numerical value. When I'm clicking the button for the second time, it is doing the ascending sorting based on the numerical value. And when I'm doing the when I'm clicking this button for the third time, it is doing the sorting uh based on the this category. Okay. So this is one method here by clicking this button sorting. There are two more buttons here. You see on the top area, this area, these two buttons are available. These two buttons are also done for sorting. So see the first button is ascending. Okay, this is for the ascending sorting and the second button is doing the descending sorting based on what? Based on the numerical value whichever numerical value use here whether it is sales or profit or whatever. Yeah, it will be you can also use these two buttons. So if I click this first button here on the top area, this is the ascending sorting based on the sales. And if I click the second button here, it is doing the descending sorting. See here I'm not having the third button for the sorting based on the category. I'm not having here third button. I'm having only two buttons either ascending or descending. Yeah. So this is also the area where you can do the sorting. Yeah. And there are also two one or two more methods here for sorting that I'll be showing you as that topic comes up for here. Yeah, if you want to give here the uh sheet name, let's say here it is written below sheet one. Now if I want to give a proper sheet name. Yeah, because sheet one doesn't look good. So here we can also double click. Yeah, below where it is written sheet one. You can double click and you can write down here column chart. Okay, type here column chart here. So yeah, this is the column chart and what we'll do now we will save this file because the same file we'll be using it uh today also and then in the other sessions also. So now uh we will save this file. Okay. So how to save the file? We'll go to as usual file. Okay, file. And in the file we are having here save and save as. We'll go for save as here. Okay. And now I'll request you to save this file in a proper folder. So you can create a Tableau uh let's say Tableau report folder or something like this. And then you can uh yeah you can save this file. But let me show you one important thing here. When you're saving the file just hold on. So see I'll I'll save it in let's say desktop folder. Okay. In the desktop I'll click on this new folder and here I'll be creating a folder which is known as simply learn tableau batch uh yeah December 2024 suppose. Okay. So I'm creating one folder here. Accordingly you can create your own folder. And now I'll be saving this file. Now what I'll do here I will save this file as uh sample supertore data set. Yeah I can give yeah you can give your own name also over here. So file name I'm giving here I'll give here day uh day two okay because today is day two so day two sample supertore data set or sample supertore uh report okay so you can give like this also so day2 sample supertore report and now what I'll do here you see that here it is written has save as type. Now in the save as type if I click the drop-down here in the save as type then there are two options here. Tableau workbook which is having the short form TWWB and the another one is known as Tableau package workbook which is known as TWWPX. Now let us understand what is the difference between dot TWW and dot uh TWWBX. See suppose if I save this file as TWWB which is known as Tableau workbook suppose. Okay, I'm not clicking the save button. Let us assume that I'm I'm saving this file as EWB. So what happens here that if I save this file now suppose if I want to share this file with you. Okay. So I can definitely share this file with you. Now if you if you download my this TWW file into your laptop and when you open this file in your laptop what will happen that it will show you one message that you have to connect the data set with this TWWB file. So remember that when you are creating a TWWB file the data set which is which we are using over here which I'm using over here that is the sample superersto data set the data set is not getting connected with this TWWP file okay when you open this file in your laptop my file in your laptop then what you have to do you have to again reconnect that sample supertore data set that's a excel file you have to reconnect with your with my file with my this Tableau file. Yeah. So that is what we mean by TWWB. The another option over here is Tableau package workbook which is known as TWWBX. What is this TWWBX? When I save this file as TWWBX, then the data set which I'm using over here, the sample super data set that also get attached with this Tableau file. So if I send you this TWWBX file and when you download it into your laptop and when you open my file, you'll not have any problem. Yeah, you don't have to connect the data set with with this file because the data set is already there or test with this file. So normally I would suggest you to save this any of your Tableau file as EWPX. Okay. So whenever I'm teaching this subject to the university students also and when they when I'm conducting their exam definitely in the exam I'll be asking them the practical question. So I always specifically mention that please save this your Tableau file with the extension TWWBX. Okay, definitely I'll be also having the data set. But for what happens that every time if there are 60 students in a class, every time I have to connect the data set and then only I can see the visualization here otherwise it will be difficult for me to see the visualization. So I always tell my university students to save the file as EWBX so that as soon as I open their file, as soon as I download their file and I open their file, I can see all the visualization then I don't have to connect any data set. Okay. Okay. So I'll also request here all of you to save this file as TWWBX. Okay. So in the TWWB no data set is connected. In the TWWBX the database is also connected with your uh Tableau file or tableau report. Okay. So I'm saving it as TWWBX and I've given this name day2 sample supererstore report. I click on save button and now it is saved. Okay, now it is saved. So this is how we are saving this file. Now I'll also show you very quickly here. If I go to this Tableau public. Okay, just focus over here. Uh is this Tableau public? No, this is not Tableau public. Uh just hold on. Yeah, let me close this file. Uh yeah, I'll also open this Tableau public. Okay, you don't have to open it. Just focus over here. Okay, so this is the Tableau public. Okay, just for your knowledge purpose here in the Tableau public here. Yeah, just focus over here. I'm I'm connecting that data set. Okay, I'm connecting that sample supertore data set here. And now here I'm dragging that order sheet. Okay, I'm not dragging here people sheet and return sheet. I'm dragging here the order sheet. Now I'm going to the sheet one. Okay, and in the sheet one I'm creating the same chart in the Tableau public. So category I'm putting over here in the column section. Sales I'm putting over here in the row section. I'm making this instead of standard I'm making it entire view and I'm doing the sorting. Okay. I'm doing the descending sorting. So see this is my Tableau public. Okay. Just Yeah. So now in the Tableau public also if I want to save this file I can go to file and in the file in the file I'm having here options like save save to tableau public then save as and save to tableau public as now see here there are four options in the Tableau public. Initially I would say that almost like six months before or one year before here in the Tableau public I was having only two options to save the file. What were the two options? Save to Tableau public and save to Tableau public as okay there was no save and save as option in the Tableau public here. So what was the initial problem with the Tableau public that if I want to save this file let's say I want to save this file on my laptop then I I could not save that file on the on my laptop with the Tableau public. I can save this file on a on the Tableau cloud platform. Tableau is having one cloud platform which is known as Tableau public. That name is also known as Tableau public. So if I'm using Tableau public, I could not save over here in my laptop. That was the earlier version. Not now. Okay. Now I can save this file. Yeah. If I click over here on save as, I can save it in my laptop on my desktop here. Okay. This is not possible. So this is a good thing. But earlier I could save only in this Tableau public. So suppose if I click here save to Tableau public as. If I click over here then what it says here Tableau public sign in. Okay. So I have to now sign in here. Now see normally if you if because you have not created any account. Uh yeah I I or if you have created the account then here you have to write down your email id. So let me write down here my email id here which I've used here. Okay. This is one of my university mail ID. Okay. So I'm I'm logging over here. I hope it should work. Yes, now it is working. So see now I have logged in and normally when you are not logged in and uh you can create your own account here in the Tableau public and then you enter into the Tableau public the cloud west platform and now here it is saying save workbook to Tableau public publishing this workbook will make it available on the Tableau public website now see there are two things here one is known as Tableau public which is a tool that we what I'm currently using over here and there There is another concept known as Tableau public website. So just now what I'm doing I'm saving this file which I have created in Tableau public and I'm putting it on the Tableau public website. Okay, make sure it doesn't contain private or confidential information. Now see this line is very very important. Make sure it doesn't contain private or confidential information. Now why this line is coming over here that also I'll now tell you. So here it is asking me workbook title. So by default it is book one. I don't want to save it as book one. I'll write down here as uh day two sample superstore report. Okay I'm giving the same name here day two sample superstore report. And now I'm clicking on save button here. What I'm doing here? I'm saving the file into the Tableau public website. So I click on the save button here. And now it is saving. Okay. Now I'll show you that website. Okay. See this is that website here. I'm bringing this website here. So see now this is my browser and what is the uh initial uh this URL over here? It is public.tablo.com. Okay. In case of PowerBI, you know that concept that is PowerBI services. Okay. So, normally we publish that uh our our report into the PowerBI services. Now, this is also a cloud-based platform from Tableau and the initial uh URL is written public.tablo uh public.tablo.com. Okay. Now, here this is the report which I published over here. Okay. So here it is written uh day2 sample supertore report by Samiria. Okay. I can also create here my profile. Okay. So see here I can create my own profile. I can put my photo over here. Yeah. Now if you remember that when I was saving this file into the Tableau public website, it was telling me that please do not use the private and confidential information. Okay. Why it was telling me this? Because now this this URL which is there. Yeah, this is now public. So anyone can see my this particular report. Anyone in this world can see my report. Yeah. So this Tableau public website is a free website. Okay. I'm not paying anything for this website and plus anyone can see my report and also I can see the other person's report also. Suppose if you uh search my name in this Tableau public website you'll get my name you'll get you you'll come to my account and then you can see all the reports which I have created over here. Okay. And I can also see your report if you have published on the Tableau public website. So that's why because this platform is open platform that's why I would strongly suggest you do not use your company data and do not publish your company data report into this Tableau public website. Okay, remember this thing because your company data are very very sensitive and if you put it over here anyone can see your report. Okay, so remember this thing only you should use the dummy data. Yeah, if you are using the sample superers store data or this global supertore data what I've shared with you or or any other dummy data then go for this thing. Okay, you use only the dummy data and you can put your report over here. Now what is the advantage of this Tableau public website? So see yesterday I told you that if you are uh writing in your CV that okay I have completed my PowerBI course I have completed the uh Tableau course that will not really help you. What you have to do you have to do your more marketing that is what I mentioned yesterday. Now how you can do the marketing that you really know about this Tableau what I used to do yeah before seven years back yeah when I was applying to various uh various uh companies and their jobs. So what I used to do that in my CV where I was writing that word Tableau in my CV that okay this is these are my skills I was giving a link on my CV. Okay. So anybody will open that my short copy of my CV. Yeah. And if they click on the Tableau word then they will come over here to this my profile and then they can see all my various reports which I have created over here. So remember that if you are planning to uh to change your job or if you are if you want to come to this data analytics area yeah and if you want to showcase your work to the recruiter then please create a proper this Tableau public profile. Okay. So here you should be having your photo. You should be writing something. Yeah. In this edit profile if I click it. Yeah. Here the LinkedIn uh link is there. Website. If you are having your own website. Yeah. If you are currently working in some organization, write on your title here. Organization. And here you can write down your bio. Here it says introduce yourself to the community. Use hashtags about your interest to make it easy for others to find you. So you have to create a proper profile over here. Okay, with your photo and everything, don't don't keep this photo blank. Okay, it's not it will not do good. Put a proper professional photo over here and then what you can do here that you can share this this link. Yeah, either you can do one thing. You can uh if you don't want to create a link in your in your CV, you can when you are uh let's say sharing your CV with your with the recruiter, you can also say that okay, please find my data visualization work in PowerBI and Tableau uh by clicking the following link. So in PowerBI also you are having the PowerBI services. Okay. So you can use that PowerBI service link and you can paste it in your email and you can also paste this link here, this URL. So what happens that when any recruiter wants to see your work? Yeah. They will click that link and then they will come over here and then they will see the visualizations and they will see the report and then during the interview they will ask okay can you explain me this report? What what was the data set? How did you create this report? Definitely this you you you'll not be creating a very simple visualization. You'll be creating a little bit complex also. So they will directly ask questions from your own report. Now see you have already created this report so you are very confident. Yeah. So maybe it is possible that your interview will be focusing only on this thing. Normally in this data analytics area yeah they'll be asking you the technical questions. There'll be technical round. So create a proper profile over here. Yeah this is the platform where you can showcase your work and this is how the recruiter will get some confidence that yes we have created so and so visualization. After once your project is also over after this course is over once your project is over please publish your report or your project over here. Yeah. And then later on whenever you are creating you are working with some different data set and you are creating some report please publish over here in the Tableau public profile in the Tableau public website. Yeah this is the platform for doing marketing. Okay. And here I can also search any other person here. Suppose if I search here, if I click on the search button, I'll show you one of the uh expert. Yeah, his name should come here. Yeah, this is one of the expert Kil Kil Aramco. Okay. So I can search over here in the Tableau public website and I can go to this person website uh or web page Kir Aramco. If I click it. So see this is one of the report which has been created by this person. These are see these are the various tabs over here. Yeah. Readal orders, office supplies, unemployment. Yeah. But actually this is not the person who is created Kil. Okay. Kiril is having a different website but a web page here. But you can see this thing. Okay. Then there is also one Indian which I like his work. His name is you see here someone has created a resume in the tableau. Yeah. Can you see this thing? Pan Talvare. Yeah. Let us see here his website his link over here and you see he has created all these things in Tableau. This is not created in word. Okay. So you can also do this thing. I'm not saying that immediately you should start with this thing but there are creative people in this world who can also do this kind of thing. Yeah, this is a great thing. Yeah, even I have to also think twice that how he has created but definitely it is possible. So you can also create this kind of rum. Even in case of PowerBI also you can create a rum in PowerBI like this. Yeah. So here you can see the work of other people and you can get lot of motivation and you can also make this favorite. If you like this uh this rum I can also make it here. Yeah, this star I can click it and when I go to this my profile. Yeah, when I go to the profile I can click on my favorite and you can see that now that person's resume is now favorite because I like this work. Okay, then you can also follow people. You see here it is written following and followers. Now I'm using here another account. This is not my real account but in my another account uh some people are following me and I'm also following other people those who are experts in Tableau I'm following them. Yeah. So here I can follow other people and if I like uh this person's work I can al also follow him. Yeah. So this kind of activity is there here in the Tableau public website. I hope that I have made you. Can you please repeat again the saving in public version once again? Yeah. So public uh here if I go to this Tableau public I have to go to file and I have to click this option save to Tableau public as save to Tableau public as if I click it and then it will if you are not logged in to Tableau public then you will you have to login with your email id and password. If you have not created a account, you have to create an account. Then you log in and then here you have to write down your workbook title means workbook name. You have to give your proper title here to the workbook and then you can click on the save button and as soon as you click on the save button you will open up this uh this uh URL. Okay, you'll it will open up the browser and it will take you to the Tableau public website. Yeah, I hope that it is clear. Okay. So this is a great platform but as I again I I'll I'll repeat that sentence that please do not uh use your company data your sensitive company data and view please yeah you can you can use it uh mean you can use your company data put it into Tableau but keep that Tableau file within your laptop only don't put it into the Tableau public website. This is very very dangerous. Okay. So this is a great platform. You can check this thing later on. Yeah. And please create a proper profile here. Yeah. If you want to uh let's say send it to your recruiter. Yeah. You should be writing something in your bio. Put some proper photo over here. Yeah. Likewise. So this is the Tableau public tool. from Tableau public we can go we can uh uh say publish the report to the Tableau public website. Now in this Tableau desktop also see now I'm in the Tableau desktop. Now in the Tableau desktop if I click on file in the file I'm having only these two options save and save as. So suppose if I have created a report in the Tableau desktop not in the Tableau public I have created the report in Tableau desktop and if I want to save it onto the Tableau public website then what should I do? So what I have to do here I have to go to this server. See there is one tab here known as server. Yeah after format there's a server. in the server I can go to here the last option tableau public and in the Tableau public I'm having that same option save to Tableau public and save to Tableau public as yeah so you should not worry that oh I'm using Tableau desktop now how should I save this file and how should I put it into the Tableau public website so to come to the server here server tab go at the bottom last option tableau public and when you come to the Tableau public you can click here save to tableau public s. If I click it yeah it will give me the I have to maybe I have to sign in here. Okay I have to sign in here and then I have to publish this uh report to the Tableau public website. Okay so remember that when you are applying to various jobs related to this data analytics then please try to create at least five to six reports. Yeah, you create five to six reports in PowerBI. You create the five to six reports in ALO. Maybe you can you can use the same data set or different data set also that is fine. Yeah. And I would like to show you one website here uh just hold on there is one website where you can get many data set because sometimes I'm getting these kind of question that okay Samir if I want to work with different data set uh where can I find the data set okay so there is definitely you can go to kegel yeah uh kegel there are a lot of website here then there is one website where I saw a lot of data set that is the website name is Maven Maven analytics. Okay, Maven analytics they are create they are having their own courses but I would not tell you to uh uh enroll for those courses but here if I go to this website just type yeah just write down this uh link uh this is name of the website that is Maven analytics maven analytics and if I go to their website here uh yeah they are they have created lot of courses here but I not go for it. But uh uh maybe discover. Yeah. Yeah. Here you see if I click on this discover and if I click on this resources in the resources I'm having here data playground. Okay. Here it says free practice data sets handpicked by Maven instructors. If I click on resources, if I click on data playground, then here you see here these are the various data sets. Okay. So these are great and I think so there are many many yeah so see how many are there 1 2 3 4 5. So five data sets per page and I think so there are total 13 so 13 fs are 65 around 64 65 data sets are there okay and they are there there are they are of different variations so you can use this and this is available free free of cost okay you click on this download button let's say if I want to go for this wine tasting data set they will see that okay how many records are there how many number of fields are where yeah uh in which type it is available. It is in CSV format. If I click on this download, it will show me here CSV and if I click on CSV and then my my downloading has started. Okay. So I'm not paying anything for this this thing. So this is a recently I saw this website mean I I I know this uh uh this Maven analytics but uh I I came to know about this data set. Okay. So likewise there are other platforms also where where you can get the data set but this is one of the good platform here Maven analytics just search in Google and then you go to their website and here you go to discover in the discover you go to resources in the resources you go for data playground and when you click on data playground you'll be getting this data sets here okay and there are lot of pages here there are 13 pages here Good. Yeah. So now let us come back over here. So see we have saved this file. Okay. So let us uh uh close this file because we'll be coming back very soon. So let us close this file. Yeah. And now I will request you that you open a blank Tableau desktop file. Either Tableau Desktop or Tableau public, whichever is fine. So I'll open up again Tableau uh Tableau 2024.3. So just open a blank Tableau file. Okay. And now we'll go one by one those concept of uh data blending uh then union and pivot table and then if time permits then we will come back to that uh sample super data set and we'll continue further. Okay. So please open a blank Tableau desktop or Tableau public file. So first of all I would like to show you here the concept known as data union. Okay, data union. So for data union we'll be using uh uh okay so see uh you already downloaded all these data sets from your LMS. So for the data union we are having this file which I've already shared with you which is known as union demo file supererstore.xls. Okay. So this data set union demo file supertore data set this will this will be connecting with the blank tableau desktop file. Okay to understand the concept of data union. So let me yeah I hope that you all opened this file. Okay blank file and now I click on this Microsoft Excel and now I select that file which is uh this one union demo file. Okay you have already downloaded. So please connect that file Excel file union demo file supertore. Click on open. Okay. Now I would like to show you that first of all that raw data set. So let me show you what is that data set containing. So see this is that data set. Okay. That that uh uh original data set here. So I opened that file. You don't have to open this file. It's not compulsory. So in this file that is union demo file supertore Excel file. You can see that here in on my screen that there are these three sheets over here 2011, 2012 and 2013. Yeah. If I open this 2011, okay, 2011 sheet. So see it is containing here country. Then there is a state. Okay. Then there's region column. Then category, subcategory, product name, sales and profit. Okay. So 1 3 4 5 6 7 8. There are eight columns over here in the 2011. Country, state, region, category, subcategory, product name, sales and profit. Okay. Now this is the data of 2011. Now if I go to the 2012 sheet, the 2012 sheet is also containing the same columns, same columns, okay? Country, state, region, category, subcategory, product name, sales and profit. Okay, but this is the data of 2012. And then if I go to the 2013, 2013 is also having the same thing. Okay. Country, state, region, category, subcategory, product, sales and profit. So here what we are having, we are having the data of three years. And now what we want to do, we want to do the analysis. Now see, I cannot do the I I I I if I do the analysis individually, let's say for 2011, 2012, 2013, if I do it separately, it doesn't make any sense here. So what I want to do here I want to add all these data of 2011 plus 2012 plus 2013 and then I want to do the overall analysis and then I want to know that okay uh say whether the sales have increased or decreased over the period of time or whether the profit has increased or decreased over the period of time. Yeah because I I I cannot do it individually here. It doesn't yeah make any sense here. So that's why I want to combine these three data set into one data set. And what is the situation here that here in these three data set the number of columns are same and the titles are also same. Remember to remember this thing the title should also be same. If here it if it is written here country. Yeah. Okay. And in the other data set if something else is written let's say it is written country name then country and country name are different according to Tableau and according to PowerBI also it is is different okay so country and country name titles are different so what I have to first of all check if I'm having these kind of scenario what I have to check that whether all the columns are having the same names in all the three field in all the three tables if here it is country then in the other two tables also you should have the country column column. Yeah, you should not have different name here, different title here. So in this situation, we are having the same number of columns, same column titles, but the data is different. Okay. So that's fine. So now what we'll do, we will combine these three tables into one table and then I will do the analysis. So here we are having the concept known as data union. And this data union is similar to the append queries technique in PowerBI. In PowerBI you must have gone through that concept of append queries. What is append queries? In append queries also we are doing the same thing. We are putting the one table below the other table and append queries is also used when you are having these kind of situation that the number of columns are same and the titles are also same. So whatever the topic that we are having in PowerBI that is known as append queries. Here in case of Tableau it is known as union data union. Yeah concept is same only the names are different. So what we'll do now we have connected this union demo supererstore file over here and we can see the three tables here three sheets. So first of all what we'll do we will bring this 2011 table over here. Yeah, bring the 2011 over here. So, see now 2011 is over here. How many fields it is having? Eight fields, eight columns. And how many number of rows are there? 3,270. Okay. So, this also I'll write down somewhere. So, 3,270 rows are there. Yeah. In the 2011. Now what we'll do I'll drag this 2012. First of all you focus on my screen what I'm doing how to do the data union. I'm dragging this 2012 over here. And now what I'm doing here see if I if I bring it over here then you can see that this noodle is created. A noodle is created. I don't want to create a noodle. I'll bring this 2012 over here. Near 2011. So see when you bring this 2012 near 2011 you see this word union. You should be able to see union. If I go a little bit far away, then I'm not able to see the union word. I have to come nearby 2011 and then I have to drop it. I have to drop this 2012 onto this word union. Yeah. So I drop it this 2012 to this union word. And now you see here this icon has changed. If I put my pointer on this 2011, what it says here? Logical table 2011 and union tables is 2011 2012. Yeah. Just put your pointer over here. Yeah. And if I double click here, if I double click, if I double click here, you can see that I can see that there is 2011 plus. Here it is written plus. It says here 2011 is made of two tables because there is 2011 plus 2012. Yeah. If I close it, if I click on this cross button here. So see this is your data union. And now you see here how many fields are there? 10 fields and 5,898 rows. Now see the number of rows have increased. So 5,8 98. Okay. See how many actual table how many actual columns are over here? 3 4 5 6 7 8. So normally there should be eight columns here. Eight fields. But now what has happened here? The number of fields have increased 10. Yeah. And why it has become 10? Then also we'll see further. So now here in this 2011 I'm having 2011 + 2012. Now what I do I drag this 2013 and I bring it over here nearby this 2011 and then I I drop it on the union area. Okay. So I drop this 2013 on this union area. And now if I put my pointer here, you see it is written logical table is 2011 and union tables is 2011 + 2012 + 2013. Okay. And now you see here 10 fields and 9,872 rows are available. So see the number of rows are getting almost double and three times. Now when we had only one table 2011 the number of rows were 3,270. When we added the 2012 to 2011 the number of rows became 5,800 something. And now when we are uh taking the 2013 and we are adding it to this union table the number of rows have increased to 9,892 rows. And these number of fields are 10 fields. Why it has become 10? Because let us focus over here. Yeah, you see here country country is there in our data set. Country, state, region, category, subcategory, product name, sales and profit. So see this eight columns. How many columns are these? Eight columns. country, state, region, category, subcategory, product name, sales and profit. So eight columns are also available in our original data set. So see when I I I add this 2011 + 2012 + 2013 in my final table I should be having only eight columns. But what you are able to see here, we are able to see here total 10 columns. Why these 10 columns have come up here? Because if you see the last two columns here, what are these last two columns? These last two columns have been created by Tableau. We have not created these last two columns. It has been created by Tableau. What is the last two columns here? First colum the the second last column is known as sheet. So see these are the sheet here. How many sheets we are having here? Three sheets 2011, 2012 and 2013. And we are also having here another column which is known as table name. 2011 12 13. So here these two columns have been created by Tableau not by us. So our actual columns are these eight columns. But because we have done the union that's why these two columns have been created by Tableau. I hope that you are able to understand this thing. Yeah, clear this point. Okay. You'll ask me a question that some we are having in the original tables only eight columns. Why here we are having 10 columns? Because of these two things because these two columns have been created by tableau. Okay. Now here we are having sheet and here we are having table name. So if you see the sheet and table name they are having the same data. Okay. So what we can do here we can hide one of these column because I don't want to have these two columns which is having the same data because both are showing you here 2011 this is 2011 and then it will show me 2012 and then it will show me 2013. So I don't want to keep both these columns. It's a data duplication here. So what I can do I can make one of these column let's say this table name column I can make it hidden. I can hide it because I cannot delete it. Okay, I can just hide it. So what I'll do, I will go to this table name column and I can just hide it. I click on hide and see now this one column is hidden. Table name is hidden. Okay. And now here it is written sheet. Now see sheet doesn't look good. Here the title is not looking good. What I can do? What are this one? 2011 12 and 13. These are ears. So instead of sheet I can double click double click the sheet and I can write down here ears. Ears. See double click here sheet and you write down here years. That's the proper title. Yeah. So I I also require this years column because if I want to do the analysis of sales and profit over a period of time, I require this years column. So instead of sheet, I change the name to years. That's all. Okay. So now I'm having how many fields? Nine fields. Nine columns and the number of records are same 9,892. So this is how you are doing the data union. Now remember this thing that in this example we were having one file, one Excel file and one Excel file was containing different sheet. It is not compulsory that every time you'll have this thing. It is possible that you may have different Excel files. One Excel file will contain one one Excel file will contain the data of 2011. Another Excel file will contain the data of 2012. Third Excel file will contain the data of 2013. So what you can do here you can bring all those Excel files one by one year. Yeah. Because this kind of situation will not be always in in in your company. Yeah. Every month you are getting one one Excel file. Yeah. So you you have to bring this Excel file over here. Okay. And then once you bring the Excel file, you'll be able to see the different sheets here in the Excel file. And then you can simply drag that sheet and create the union. That's all. Okay. The concept is same. But here in this example, we are having one Excel file and one Excel file is containing various sheets. Yeah. But it's not compulsory every time. Yeah. So once we have created this data union. Yeah. Now I can go to the sheet one below. We can click on the sheet one here. And now in the sheet one what I can do? I can drag let's say this years. I drag the ears in the columns and I can drag the sales sales in the rows area. So see years I can put it in the columns and I can drag the sales in the rows area and now this is a column chart. Okay, let me make it entire view. Entire view. I'll do the sorting. You know this sorting button. Either you can click these two sorting button or this button. The sorting. And now I can see that in 2013 the sales was maximum followed by 2011 and then 2012. Yeah, I can also create a line chart here if you want. I can go to show me in the show me. If I click here, show me, I can click on this line chart. This one. Okay, I can click on this line chart or for lines. Okay, lines. Okay, now sorry lines, it requires one date field here. Date field. Okay, so I cannot create a line chart here. Why? Because see this is here we are having only years there's only year 2011 12 and 13 we are not having the exact date if here we would have some date column like order date ship date and I could have created the line chart but here you can see that I cannot click this line chart here because it is telling me that for line chart I require one date field okay so there's a difference here date field is different and this year column is different it is only containing here year it's not a date. Yeah. So I can create this kind of column set and I can do this kind of analysis. Yeah. So this is what we mean by data union. I hope it's clear. Any question from your side? Yeah. Anything which you could not understand in this data union. So first of all you bring all the sheets or you bring all the Excel files to your tableau. You connect with your Tableau and then you uh do the data union in the data source area. Let me click on this data source here. You do the union over here and then yeah you can come to the sheet one and then you can create such kind of thing. We use union when data is more than one. Yeah definitely. Yeah because if you're having one one file it doesn't make any sense. Yeah. So you should have at least two uh data sets which are having the same number of columns and same titles and you can do the data union. data union is clear. So what you can do if you want to save this file separately you can click on file save as and let me also save this file. Yeah for each topic I want to create a separate file so that you can see those files properly. Okay. So I'll save here this file as uh day2 and I write down here data union. Okay, just for my uh reference here day2 data union and I save here as EWBX. Remember this point EWBX. Now see one of the advantage of TWWB is this that TWWB file will be smaller file. Smaller file means it does the the size of that file will be small. Why? Because you are not attaching the data set in the TWWB while the TWWBX file will be always a larger file a big size file. Why? Because the data set is also attached over here. Okay. Okay. So, our data set is containing only 10,000 record. But if you're having a data set which is containing let's say uh 100,000 record then definitely your TWWBX file will be very very large enough. Okay. So, you have to decide. Yeah. I am not saying that TWWB file is a very bad file, bad option. The advantage that we get with the EWB file is that that the file size will be small because there is no data set attached with that file. Okay. If you if you know that your colleague is already having that original data set then you can just send them the TWWB file. But remember that this this file that you are sending it to your colleague it is because that your colleague will also help you in creating the visualization. If you are sharing this file with your users with your business user then you should not say or say you should not send this TWWBX file. If you want to share this report, this Tableau report with your business users then either you can use Tableau server if your company is very large enough or you can use one another concept known as Tableau online. In the Tableau online you can create your account and then other people can also create their account and then I can share this file with my other business users through the Tableau online. Tableau online is much more cheaper because in Tableau online I am just giving the money per account. Okay. So if my organization is small and if there are let's say 20 users only in my organizations who are using Tableau I can go for Tableau online. But if there are let's say 500 users 600 users 1,000 users then it makes sense to go for Tableau server. Okay. So in the Tableau server you'll have the data set also. You can store the data set. You can also store the report and you can also provide the access to the reports in the Tableau server. So these are the advantages of Tableau server but they are very costly. Remember this point. Okay. You can check with the Tableau team. I don't know the exact figure. Yeah. So let me save this first of all this file. I'll save it with TWWBX day2 data union. Okay, let me check here. Uh, Tableau server pricing. Let us see if something is there here. Uh, tableau pricing. I don't know whether it will be there or not. Normally, they will not share this information. You have to ask them specifically and then only they'll be able to share. Okay. So here also Tableau server. Yeah. Tableau server also you can try for free if you want. Yeah. But uh there's also this Tableau online. Okay. This is the new Tableau online. Okay. So these are the various pricing here. You can check it this different pricing here. Enterprise viewer. Uh see here uh suppose if you are using if you are providing the license to your user business user. Okay. Now see business user will not be creating any visualization. they'll not be creating any Tableau uh report. So for them these kind of licenses are very good that is enterprise viewer license. Okay. This is $35 per user per month basis and they are build annually. Okay. Uh and if you want to if you want to give the license a Tableau license to a developer Tableau developer then the Tableau developer should have this enterprise explorer. Okay. So that is costing $70 per user per month basis. Okay. But just for viewing purpose you require this license which is cheaper almost. Yeah. This is half. Okay. So here you can save your money. You have to decide that okay how many people will be developing the uh the report and how many people will be viewing the report. So for viewing you are having this license and for developing you are having this license. And here it is little bit much more is expensive. Discover insight with powerful suit of product that support your end to end. Yeah. So here you'll be having some extra features here. I have to go through this thing. Yeah. But uh here it says Tableau desktop. It includes Tableau desktop, Tableau prep and one creator license. Yeah. So here you are having additional features. That's why they are costing here 115 uh uh dollars per user per month basis. Okay. So you can check this thing. Tableau pricing. So I think so Tableau this uh union part is clear. We'll open another Tableau desktop file a new file. And now we'll be going for the concept known as pyro table. What is this pyro table? So now we'll be going for the next concept which is known as pivot table. Okay. Now all of you you know this pivot table because we discussed this thing in the Excel uh course. Now here we can also do the pivoting of the table pivoting. So what we'll do now we will use this data set. Which data set here? Let me show you the data set. We'll be using this data set which is known as p data.xls. Okay. So now we'll be connecting this excel file p data doxls with the tableau file with a blank tableau file. Yeah. If you have not downloaded this data set, please download it immediately and we connect it with our this Tableau desktop or Tableau uh public. Let me close this file. Okay. So, just open a blank Tableau file. I click on Microsoft Excel. And now I'll be connecting that uh this one. Yeah, pivot data or pivot data whatever you say. Okay. So pivot data or pivot data this Excel file I'll be connecting with Tableau desktop or Tableau public. So see here you can see that we are having sheet one. Now see if your Excel file is containing only one sheet then automatically it will come over here. You see here I I I did not drop this sheet one here. It automatically came because in my Excel file if I open that Excel file that P table or P data let me show you that P data Excel file. So see this is that Excel file which I'll be connect which have which I have now connected with Tableau. So this Excel file I have just created a demo. Okay, this is a demo file. So here there are some products. Okay, and there are these you can assume that these are the sales figures. Sales figures for various financial year. So financial years 17, 18, 19, 20 and 21. And these are the products. Okay, phone, television, PlayStation, home theater, router, smartwatch, laptop. This is just a demo file here. So now here you can see that I'm having separate columns for each of the year. Yeah. Now if I I have connected this file okay with this Excel sorry I have connected the Excel file with the Tableau desktop. Now here we are having this separate columns. So whenever you are having this kind of situation where you are having separate columns for each of the year or separate columns for each of the month then this will uh if you directly use this data set and if I go to sheet one suppose if I go to sheet one here and now if you tell me that okay uh yeah if you ask me that okay Samir I want to uh see the sales figures I want to analyze whether over a period of time whether the sales increased or decreased for each of the product. Yeah. So I want to do the I want to create here uh let us say a column chart. Okay. I and I want to do the analysis of the sales figure for each of the year. So here what is happening that if I go to seat one I can see these various columns. Okay. So suppose if I put this product into the columns area then what I have to do? I have to drop here 2017, 2018, 2019. You see the issue here? I have to put here separately each of these uh fields. And now I'm getting these kind of visualization. It is not not making any sense here. Yeah, I cannot analyze these kind of visualization. I want to create here a column chart for each of the product and I want to analyze their sales figures for each of the year. Okay. So this is the issue here that I can if I keep this year separately then it will not help me. So what I want to do I want to remove this. See first of all I'll show you one technique here. If you have created some visualization here and if you want to delete that visualization, how to delete the visualization, you are having one button here. Yeah, this is that button which is on the left hand side of this fab button. This button, if you click this button, then this visualization will go away. Okay, so if I click on this button here, the visualization is gone. Very easy. Okay. So remember this button here. If you want to clear it is, it says here clear sheet. Okay. So I'll go back to the data source below. You can see here at the bottom area bottom left corner data source. I click on data source. So just now what is happening that I I I cannot keep this years column separately. So what I want to do now here I want to do the pivoting. What is potting? Here I want to convert these five columns into five rows. I repeat I want to convert the five columns into five rows. Now in case of PowerBI uh in case of PowerBI have you gone through that concept of p and unp? Yeah. In PowerBI we have one concept known as p and unp. Have we gone through that concept here? Yes. Okay. So p means in case of powerbi p means you are converting the rows into columns and in case of powerbi the unpivoting means you are converting the columns into rows. So in powerbi we are having separate two topics p and unpivot while in case of uh tableau both p and unpivot are overall known as p. Here we don't have that concept of unpivot. Yeah. Though we do the unpivoting in unpivoting here what I'm doing I'm converting the columns into rows. So it is unping but according to Tableau it is known as P. Okay. So here we don't have separate concept. The whole thing is known as P. Whether I do the potting or whether I do the unping in Tableau it is overall known as potting. So how to do the potting? Here you select this first column 2017 and now you press the shift button because see you want to select all these five columns you press the ship you select the first column 2017 press the shift button and now you select the last column here 2021. Okay. When you select the last column here by pressing the ship button you see that all the five columns are selected. So even if you're having 100 columns you should not worry. Select the first column. Press the shift button and then you select the last column and then all these columns are selected. Yeah. Now what we want to do? We want to do the we want to convert these columns into rows. So here I have to click this any of this drop-own arrow. Yeah. Either I can click here or here. Anyone I can click the drop- down arrow. And now here we have this option known as p. P. Here you see here there's option P. Click the drop-down. Any one of the dropdown click on P. When you click on P when you click on P here you are now having here see phone phone. See now there are different records here. There there are duplicated record but why they are getting duplicated? Because here you are having five years and these are the pivot fields values. Okay. So see these now these two columns have been created. pivot fields name and pivot fields value. These two titles are given by Tableau. Okay. In case of PowerBI also this happened that when you are doing the unpivoting or pivoting PowerBI is giving its own title. So now what we can do is pivot fields name I can double click and I can write down here financial year or FY. Okay, I can write down here FY financial year and here I can double click pivot table pivot uh fields values. I can double click and I can write down here let's say sales because these are the sales values. So I write down here sales. So see this is the product column, this is financial year and this is the sales. Okay. So I have changed the title here. And now my job is done. I can go to the sheet one. I go to the sheet one. And now I can drag here. I can drag this financial year in the columns area. And I can drag the sales here. Sales in the rows area. And now I can see the column chart. Yeah, I can make it entire view and entire view. And now I can click this sorting. You see here 2020 year 2020 is having the highest sales followed by 2019, 2021, 2017 and 2018. I did the sorting here. So what I have done here I put the financial year FY into the columns area and I put up the sales. And now you see here it is very easy. So this is what you can do with the pivoting that when you are having many columns like this. So it is very difficult to analyze all those columns together. So convert those columns into rows by doing the potting and then you can put it into the visualization. This is the concept known as p. Suppose if you are having uh two columns like male and female. Yeah. So instead of keeping those two columns separately, what you can do? You can select those two columns male and female do the potting and then you can create a gender column. Okay? So there will be one gender column and then there will be one numerical column. Numerical column it can be sales profit anything. Yeah. So rather than keeping those two separate columns male and female convert it into uh do the pivoting and then you create those two columns. One is gender column and once you have the gender column then you can do the analysis that okay you want to see uh gend uh that which which uh gender is having how much sales or which gender is generating how much sales. Yeah. So it is better rather than keeping those two separate columns and then putting what over here. It is difficult. So you can do this potting in some some situations like this. So please save this file always. So file save as and I'll save it as TWWPX. Okay. And I'll use this one that is uh day2 pivot data. I'll give it like this name day2 pivot data. Click on save button and save it as TWWBX. Pyro data. This is the file. You can close it. Okay. And now finally we'll be going for the uh next topic here. Maybe it will be the final topic when and let us see if we are having some time we will switch back to that sample superers store data set but now I'll be going for the next topic which is known as data blending okay data blending here so for data blending we'll be using these two files that is office sales doxls and another fine will be coffee sales okay so office sales and coffee sales these two files will be connecting with our blank Tableau desktop file. Okay. So we are going for the next concept which is known as data blending. Now let me see some theory part over here. See we have seen this union part. Union we have already seen. Okay. Now we are going for the data blending. Okay. So what is data blending here? Data blending it says that blending is a method of combining related data from multiple sources in a single view to analyze it. So it is a method of combining related data. Now related data what do you mean by related data? Let's say I'm having a employee data. I'm having a department data. Okay. So there are two tables here. Employee table and the department table. Now they are somewhat related. Okay. So employee data will also containing the department information. Let's say if I'm working in marketing department then it will show me that okay in in my employee data it will show me that okay employee ID 101. Yeah. Then it will write my name and surname Samadia. Then it will show that okay I'm working in marketing department. And then it will show other details about me. Okay. the salary and the gross salary and the net salary and then there is also another table which is known as department table. In the department table only the department number and the department name will be written and their location will be written. Okay. So if the marketing department is there that the marketing department ID will be 101 or 01 let's say the department name will be marketing and the location will be let's say Frankfurt. Okay. So this is how the this kind of related tables if you're having and if you want to bring it together in Tableau remember that this the tables here that we are bringing over here for data blending the number of columns are not same. The titles of those columns are not same. Okay. In the data union what we saw that in the data union all uh the number of columns were same and the titles were also same. So we went for data union but in the data blending that's not the situation. Employee table will contain 10 columns or 15 columns and department table will contain three columns. But what is the main purpose over here in the data blending that when I'm connecting one table with another table yeah then I should be having one common field minimum one common field. There should be one common column between the two tables. Then only I can do the data blending. Yeah. And both are coming from both can come from different data sources. One one will be coming from SharePoint. Another will be coming from from let's say SQL server or one is coming from Oracle server. Second one is coming from SQL server. I can connect those two tables with the help of data blending. and both the tables are containing different columns and different column numbers. Okay, in that case we go for the data blending. Okay, so here it says data blending is a method of combining related data from multiple sources in a single view to analyze it. Yeah. So this is some primary data source, secondary data source. There is also one more table from secondary data source. And then here it's it says tableau identifies the common dimensions within the data source. Common dimension means the common field. What which is the common field between the two tables and then with the help of this common field it will connect the two tables and that two tables will be connected with the third table. The whole table will be connected with the fourth table likewise. Okay. So this is what we mean by data blending. And now I'll show you the practical part. So let me open a blank tableau desktop file. You can open a blank tableau desktop file. Now you see here if you are having the trial period every time when you open this Tableau desktop then it will give you this kind of message this window here. Your product trial ends in 13 days. You can either continue trial or activate the product uh using your product key or uh credential. Okay. So I click on continue trial. Okay. So every time it is reminding us that you don't have the actual version. You are having you you are using the trial period here. So now what we'll be doing here we'll be connecting those two data set. I've already mentioned this data set office sales and coffee sales. One by one we'll be connecting here. Yeah. So first of all we'll be connecting let's say coffee sales suppose just an example okay so I click on Microsoft Excel and I click here let's say coffee sales the first file click on coffee sales I click on open so here you can see that we are having the coffee sales that's the file name coffee sales is the file name and within this file we are having one sheet which is known as coffee chain sales This this is the sheet name. Let me show you that file. If I open that file, Excel file you see here this is that Excel file. Okay. So this is that coffee sales file and coffee sales files is containing the sheet known as coffee chain sales sheet. And here what we are having we are having the product type product state type region and coffee sales. So these are the various product type like coffee espresso yeah herbal tea and tea. Uh let me open that another table. Okay, that is the office sales. So this this is that office sales file which I have opened. On the left hand side you can see the coffee sales on the right hand side you can see the office sales. So in the office sales also we have here state code, state, market, market size, territory and office sales. Now see here I have given some color. There is a yellow color here there's a green color. So what is this yellow color here that here it is showing me that there are these two columns which are common. Okay, this state column is also available in the coffee sales and in the office sales also we are having the state column. So as I said earlier that for the data blending you require at least one common column. Without that column you cannot do any data blending. You require at least one common column. Yeah. So state column is here is common but also you can see here that we are having the uh this one that is the uh uh region column. You see here there is a region column. In the region column also we have here northeast, west, south. Okay. And here we have a column which is titled as territory column. But if you see the territory column it is also having the same data northeast, west, south. So the titles are different region and here it is territory but the data is same. So here we can see that there are two columns which are common between the two tables state column and the region column. Okay. So we we we have to remember this this information. Now what I do I go to this uh yeah coffee sales. Okay. So I have brought here the coffee chain sales. Yeah. And this is the six fields and 13 rows. Okay. So this is this is there. Now what we do that now I want to I want to now bring the office sales here. I brought here the coffee sales and now I have to bring the uh office sales here file. So what I have to do now? You see here there is an there is one cylinder here on the top left corner here there is a cylinder. I have to click that cylinder. this above area I click the cylinder and in the cylinder I can see this coffee chain sales bracket coffee sales and now it is giving me another option known as new data source. Yeah. So click this this cylinder icon drop down and now you click this new data source. Once you click on the new data source yeah when you click on the new data source then you are getting this blue dialog box again. What you have to do? You have to click this Microsoft Excel again because your file is Microsoft Excel. This office sales is also Microsoft Excel. So I click on Microsoft Excel here. And now what I have to do, I have to go to that folder where my database is available. And now I have to select this office sales. Okay, I select this office sales here. And once I select the office sales, I click on open. And now you see here this is my office sales. The sheet name is office city sales and see it is having six fields and 18 rows. Okay. So this is how we bring the two files one by one. First of all I brought the coffee sales file and then I click on this icon this uh cylinder icon. Now you can see that I'm able to see the two files here coffee sales and office sales. But if I want to bring another file, I have to click here this button, new data source and it will come over here. Clear. Yeah. Now I have brought both the files to Tableau. Now what we have to do? We have to click on the sheet one here below. Click on the sheet one. when you click on the seat one. So now here you can see on the top area this area here you can see that we are having both the files or both the data set you can say coffee sales and office sales. Now see if I click on this coffee sales this first file first data set I can see all the uh the the dimensions and measures of the coffee sales. If I click here office sales, I can see all the dimensions and measures of the coffee sales. Okay, this is how I can see this thing. Now what I'll do, I will click on coffee sales. And now what I have to do that I have to create the relationship here. Once I bring both the files, yeah, to tableau, then I have to create the relationship. How I can create the relationship? By by connecting the common field between the two tables. Which are the common fields over here? state state and region territory. Okay. So I have to tell Power Tab Tableau that these are my common field. Okay. So I have to create the relationship here. So for creating the relationship here I have to go to the uh data. Click on this data tab here above. Okay. On the top area after file you can click on the data tab. In the data tab you are having one option here known as edit blend relationship. Edit blend relationship. Okay. So click on the data tab and you click here edit blend relationship. And now here you can see this dialog box which is known as blend relationship. In the blend relationship it says here blend relationship determine how data from secondary data sources are joined with primary data source. Now here in my case my primary data source is coffee sales because I selected already the coffee sales here on the top area. So my primary data source is coffee sales and my secondary data source is office sales. Now in your case if you are having primary data source as office sales and if your secondary data source is coffee sales you don't worry. Yeah you can go for any one of the primary data source. So primary data source in my case is coffee sales and secondary data source is offices. Now here you can see that it is written here state. So Tableau has already identified the common field between the two tables state. Okay. But Tableau has not identified the another common field which is region and territory. Why? Because because the titles are different. Okay. If the titles, if the column titles are different, Tableau will not be able to identify. But now we have to tell Tableau that no this region and territory is also a common field between the two tables. Just like state state, region and territory are also common field. So here we can see state that's fine. But now I want to create here another relationship between the region and the territory. Now how to create the relationship? I have to go to this. See on the top area you can see here automatic and custom. When automatic is there then automatic in automatic mode Tableau will identify the common field which are having the same name. So see in automatic it is showing you state state. But now if I want to create the relationship between region and territory I have to click here custom. I have to click here custom. Select here custom option. And once you select the custom option then you have to click here below add button. Okay. Click on the add button here. After clicking on custom here you click on add button. And when you click on add button then here it says add obledit field mapping. So now you have to tell Tableau that this region and territory they are matching. Okay. So here it is showing me primary data source. Here it is showing me secondary data source. What I have done here I have selected here custom again I'm repeating the step. Ive selected here custom option and then I have clicked on the add button. I click on add button. Then it this comes up over here this dialog box. Now here I have to select region on the left hand side or if you are having territory on the left hand side you select territory here and here I select territory. So see region and territory you select like this. So this is how we can tell manually Tableau that this region and territory they are linked they are the common field. So region I select here territory I click on okay button and now you can see here that field has also come up here region territory and state state that's all okay it's not compulsory that you have to select you have to bring here another common field also you can also just keep it here state that's also fine no issues okay it's not compulsory that you should have two common field minimum one common field has to be there but here in this case we are having two common fields Now once I I I have identified the two common fields I have to click on okay button. Now click on okay button. Okay. So now these two tables coffee sales and office sales they are connected with each other with the help of that common field state and territory region. Now what we do we create the visualization here. Let's say the state. Okay, let me drag here the state. I put it here in the columns area. Okay, and then or let me put the state in the rows area because I want to create a uh bar chart. So, I put the state. See, currently I have selected here coffee sales on the top area. I've selected here coffee sales and I drag here. I drag the state in the row section because I want to create a bar chart. And then what I do, I drag this coffee sales. Okay, this coffee sales I put it over here in the columns area. Drag the coffee says in the columns area. And now you can see that the bar that is created. I can make it entire view. Okay, make it entire view. And now you can do the sorting. Yeah, you can click this descending sorting. So I can see here that connecticut is having the highest sales coffee sales and the lowest is selenoise. Okay. So I have just dragged the coffee sales. I have dragged the set over here. Yeah. And I have created a bar chart and I've done the sorting by clicking this button. Either you can click this button these two buttons as we know. Or you can go to this x-axis area and in the x-axis area where you are having the coffees you can click that button for sorting. Now you see here when I'm when I'm dragging these fields here from the coffee sales you see that this cylinder just check this cylinder here of the coffee sales it is having a blue tick mark here. Yeah there's a blue tick mark here